We present a methodology for conditional control of human shape and pose in pretrained text-to-image diffusion models using a 3D human parametric model (SMPL). Fine-tuning these diffusion models to adhere to new conditions requires large datasets and high-quality annotations, which can be more cost-effectively acquired through synthetic data generation rather than real-world data. However, the domain gap and low scene diversity of synthetic data can compromise the pretrained model's visual fidelity. We propose a domain-adaptation technique that maintains image quality by isolating synthetically trained conditional information in the classifier-free guidance vector and composing it with another control network to adapt the generated images to the input domain. To achieve SMPL control, we fine-tune a ControlNet-based architecture on the synthetic SURREAL dataset of rendered humans and apply our domain adaptation at generation time. Experiments demonstrate that our model achieves greater shape and pose diversity than the 2d pose-based ControlNet, while maintaining the visual fidelity and improving stability, proving its usefulness for downstream tasks such as human animation. Our code is available at: https://ivpg.github.io/humanLDM.

The semantic similarity between documents of a text corpus can be visualized using map-like metaphors based on two-dimensional scatterplot layouts. These layouts result from a dimensionality reduction on the document-term matrix or a representation within a latent embedding, including topic models. Thereby, the resulting layout depends on the input data and hyperparameters of the dimensionality reduction and is therefore affected by changes in them. Furthermore, the resulting layout is affected by changes in the input data and hyperparameters of the dimensionality reduction. However, such changes to the layout require additional cognitive efforts from the user. In this work, we present a sensitivity study that analyzes the stability of these layouts concerning (1) changes in the text corpora, (2) changes in the hyperparameter, and (3) randomness in the initialization. Our approach has two stages: data measurement and data analysis. First, we derived layouts for the combination of three text corpora and six text embeddings and a grid-search-inspired hyperparameter selection of the dimensionality reductions. Afterward, we quantified the similarity of the layouts through ten metrics, concerning local and global structures and class separation. Second, we analyzed the resulting 42 817 tabular data points in a descriptive statistical analysis. From this, we derived guidelines for informed decisions on the layout algorithm and highlight specific hyperparameter settings. We provide our implementation as a Git repository at hpicgs/Topic-Models-and-Dimensionality-Reduction-Sensitivity-Study and results as Zenodo archive at DOI:10.5281/zenodo.12772898.

Point clouds are widely used as a versatile representation of 3D entities and scenes for all scale domains and in a variety of application areas, serving as a fundamental data category to directly convey spatial features. However, due to point sparsity, lack of structure, irregular distribution, and acquisition-related inaccuracies, results of point cloud visualization are often subject to visual complexity and ambiguity. In this regard, non-photorealistic rendering can improve visual communication by reducing the cognitive effort required to understand an image or scene and by directing attention to important features. In the last 20 years, this has been demonstrated by various non-photorealistic rendering approaches that were proposed to target point clouds specifically. However, they do not use a common language or structure for assessment which complicates comparison and selection. Further, recent developments regarding point cloud characteristics and processing, such as massive data size or web-based rendering are rarely considered. To address these issues, we present a survey on non-photorealistic rendering approaches for point cloud visualization, providing an overview of the current state of research. We derive a structure for the assessment of approaches, proposing seven primary dimensions for the categorization regarding intended goals, data requirements, used techniques, and mode of operation. We then systematically assess corresponding approaches and utilize this classification to identify trends and research gaps, motivating future research in the development of effective non-photorealistic point cloud rendering methods.

Abstract While methods for generative image synthesis and example-based stylization produce impressive results, their black-box style representation intertwines shape, texture, and color aspects, limiting precise stylistic control and editing of artistic images. We introduce a novel method for decomposing the style of an artistic image that enables interactive geometric shape abstraction and texture control. We spatially decompose the input image into geometric shapes and an overlaying parametric texture representation, facilitating independent manipulation of color and texture. The parameters in this texture representation, comprising the image’s high-frequency details, control painterly attributes in a series of differentiable stylization filters. Shape decomposition is achieved using either segmentation or stroke-based neural rendering techniques. We demonstrate that our shape and texture decoupling enables diverse stylistic edits, including adjustments in shape, stroke, and painterly attributes such as contours and surface relief. Moreover, we demonstrate shape and texture style transfer in the parametric space using both reference images and text prompts and accelerate these by training networks for single- and arbitrary-style parameter prediction.

In 2016, BitMEX introduced a novel type of crypto derivates – Perpetual Swaps, i.e., futures with an infinite term. Perpetual swaps provide a new strategic risk management tool for cryptocurrencies due to their custody-free nature, high leverage, and funding mechanism, but there has been little quantitative analysis on the their benefits. In this paper, we introduce a trading strategy that combines a Quanto Perpetual Swap with a spot position to benefit from the funding mechanism. We compare our strategy with a long-only investment in the underlying cryptocurrency and a similar strategy based on Linear Perpetual Swaps to evaluate their performances in a large-scale backtest covering the years 2021 and 2022. Our analysis shows that our strategy generates positive returns in bullish market phases of the underlying with lower volatility.

Abstract Ground point filtering on national-level datasets is a challenge due to the presence of multiple types of landscapes. This limitation does not simply affect to individual users, but it is in particular relevant for those national institutions in charge of providing national-level Light Detection and Ranging (LiDAR) point clouds. Each type of landscape is typically better filtered by different filtering algorithms or parameters; therefore, in order to get the best quality classification, the LiDAR point cloud should be divided by the landscape before running the filtering algorithms. Despite the fact that the manual segmentation and identification of the landscapes can be very time intensive, only few studies have addressed this issue. In this work, we present a multistage approach to automate the identification of the type of landscape using several metrics extracted from the LiDAR point cloud, matching the best filtering algorithms in each type of landscape. An additional contribution is presented, a parallel implementation for distributed memory systems, using Apache Spark, that can achieve up to $$34\times$$ 34 × of speedup using 12 compute nodes.

Topic models are a class of unsupervised learning algorithms for detecting the semantic structure within a text corpus. Together with a subsequent dimensionality reduction algorithm, topic models can be used for deriving spatializations for text corpora as two-dimensional scatter plots, reflecting semantic similarity between the documents and supporting corpus analysis. Although the choice of the topic model, the dimensionality reduction, and their underlying hyperparameters significantly impact the resulting layout, it is unknown which particular combinations result in high-quality layouts with respect to accuracy and perception metrics. To investigate the effectiveness of topic models and dimensionality reduction methods for the spatialization of corpora as two-dimensional scatter plots (or basis for landscape-type visualizations), we present a large-scale, benchmark-based computational evaluation. Our evaluation consists of (1) a set of corpora, (2) a set of layout algorithms that are combinations of topic models and dimensionality reductions, and (3) quality metrics for quantifying the resulting layout. The corpora are given as document-term matrices, and each document is assigned to a thematic class. The chosen metrics quantify the preservation of local and global properties and the perceptual effectiveness of the two-dimensional scatter plots. By evaluating the benchmark on a computing cluster, we derived a multivariate dataset with over 45 000 individual layouts and corresponding quality metrics. Based on the results, we propose guidelines for the effective design of text spatializations that are based on topic models and dimensionality reductions. As a main result, we show that interpretable topic models are beneficial for capturing the structure of text corpora. We furthermore recommend the use of t-SNE as a subsequent dimensionality reduction.

We present a novel method for the interactive control of geometric abstraction and texture in artistic images. Previous example-based stylization methods often entangle shape, texture, and color, while generative methods for image synthesis generally either make assumptions about the input image, such as only allowing faces or do not offer precise editing controls. By contrast, our holistic approach spatially decomposes the input into shapes and a parametric representation of high-frequency details comprising the image’s texture, thus enabling independent control of color and texture. Each parameter in this representation controls painterly attributes of a pipeline of differentiable stylization filters. The proposed decoupling of shape and texture enables various options for stylistic editing, including interactive global and local adjustments of shape, stroke, and painterly attributes such as surface relief and contours. Additionally, we demonstrate optimization-based texture style-transfer in the parametric space using reference images and text prompts, as well as the training of single- and arbitrary style parameter prediction networks for real-time texture decomposition.

Real estate is the largest asset class and is equally popular with professional and retail investors. However, this asset class has the disadvantage that it is very illiquid, and investments have a high entry barrier in terms of equity. The adoption of the Electronic Securities Act in 2021 by the German Bundestag has created the legal framework for tokenizing real estate assets and their management using digital ledger technology in Germany. In this paper we describe a business concept for managing ownership and business transactions for real estate in Germany using blockchain technology. Besides its possibilities, we present a market analysis that comprises existing approaches and discusses legal limitations specific to the country.

Offers to buy and sell cryptocurrencies on exchanges are collected in an order book as pairs of amount and price provided with a timestamp. Contrary to tick data, which only reflects t he l ast t ransaction p rice o n a n e xchange, t he order book reflects t he m arket's a ctual p rice i nformation a nd the available volume. Until now, no system has been presented that can capture many different order books across several markets. This paper presents Hephaistos, a system for processing, harmonizing, and storing massive spot order book data from 22 centralized crypto exchanges and 55 currency pairs. After collecting the data, Hephaistos aggregates several order books in a so-called Unified O rder B ook, w hich i s t he f oundation f or a S mart Order Routing algorithm. As a result an order is splitted across several exchanges, which results in a better execution price. As component of a high-frequency trading system, Hephaistos captures 32 % of the total daily spot trading volume. We provide examples with data from two exchanges that show that the Smart Order Routing algorithm significantly r educes t he slippage.

Trading for a currency pair on centralized crypto exchanges is organized via an order book, which collects all open buy and sell orders at any given time and thus forms the basis for price formation. Usually, the exchanges provide basic visualizations, which show the accumulated buy and sell volume in an animated 2D representation. However, this visualization does not allow the user to compare different order books, e.g., several order book snapshots. In this work, we present OrderBookVis, a 2.5D representation that shows a discrete set of order books comparatively. For this purpose, the individual snapshots are displayed as a 2D representation as usual and placed one after the other on a 2D reference plane. As possible use cases, we discuss the analysis of the temporal evolution of the order book for a fixed market and the comparison of different order books across multiple markets.

Most cryptocurrencies are bought and sold on centralized exchanges that manage supply and demand via an order book. Besides trading fees, the high liquidity of a market is the most relevant reason for choosing one exchange over the other. However, as the different liquidity measures rely on the order book, external events that cause people to sell or buy a cryptocurrency can significantly impact a market's liquidity. To investigate the effect of external events on liquidity, we measure various liquidity measures for nine different order books comprising three currency pairs across three exchanges covering the entire year 2022. The resulting multivariate time series is then analyzed using different correlations. From the results, we can infer that as a cryptocurrency's market capitalization and the exchange's trading volume increases, so does its liquidity. At the same time, only a moderate correlation of liquidity between exchanges can be observed. Furthermore, our statistical observations show that external events, particularly the events around FTX and the Terra Luna crash, caused significant changes in liquidity. However, depending on the exchange's size and the cryptocurrency's market cap, the liquidity took a shorter or longer time to recover.

Abstract Image stylization has seen significant advancement and widespread interest over the years, leading to the development of a multitude of techniques. Extending these stylization techniques, such as Neural Style Transfer (NST), to videos is often achieved by applying them on a per‐frame basis. However, per‐frame stylization usually lacks temporal consistency, expressed by undesirable flickering artifacts. Most of the existing approaches for enforcing temporal consistency suffer from one or more of the following drawbacks: They (1) are only suitable for a limited range of techniques, (2) do not support online processing as they require the complete video as input, (3) cannot provide consistency for the task of stylization, or (4) do not provide interactive consistency control. Domain‐agnostic techniques for temporal consistency aim to eradicate flickering completely but typically disregard aesthetic aspects. For stylization tasks, however, consistency control is an essential requirement as a certain amount of flickering adds to the artistic look and feel. Moreover, making this control interactive is paramount from a usability perspective. To achieve the above requirements, we propose an approach that stylizes video streams in real‐time at full HD resolutions while providing interactive consistency control. We develop a lite optical‐flow network that operates at 80 Frames per second (FPS) on desktop systems with sufficient accuracy. Further, we employ an adaptive combination of local and global consistency features and enable interactive selection between them. Objective and subjective evaluations demonstrate that our method is superior to state‐of‐the‐art video consistency approaches. maxreimann.github.io/stream‐consistency

Software projects under version control grow with each commit,accumulating up to hundreds of thousands of commits per repository. Especially for such large projects, the traversal of a repository and data extraction for static source code analysis poses a trade-off between granularity and speed.

The number of software projects developed collaboratively on social coding platforms is steadily increasing. One of the motivations for developers to participate in open-source software development is to make their development activities easier accessible to potential employers, e.g., in the form of a resume for their interests and skills. However, manual review of source code activities is time-consuming and requires detailed knowledge of the technologies used. Existing approaches are limited to a small subset of actual source code activity and metadata and do not provide explanations for their results. In this work, we present CodeCV, an approach to analyzing the commit activities of a GitHub user concerning the use of programming languages, software libraries, and higher-level concepts, e.g., Machine Learning or Cryptocurrency. Skills in using software libraries and programming languages are analyzed based on syntactic structures in the source code. Based on Labeled Latent Dirichlet Allocation, an automatically generated corpus of GitHub projects is used to learn the concept-specific vocabulary in identifier names and comments. This enables the capture of expertise on abstract concepts from a user's commit history. CodeCV further explains the results through links to the relevant commits in an interactive web dashboard. We tested our system on selected GitHub users who mainly contribute to popular projects to demonstrate that our approach is able to capture developers' expertise effectively.

Based on the assumption that semantic relatedness between documents is reflected in the distribution of the vocabulary, topic models are a widely used class of techniques for text analysis tasks. The application of topic models results in concepts, the so-called topics, and a high-dimensional description of the documents. For visualization tasks, they can be projected onto a lower-dimensional space using dimensionality reduction techniques. Though the quality of the resulting point layout mainly depends on the chosen topic model and dimensionality reduction technique, it is unclear which particular combinations are suitable for displaying the semantic relatedness between the documents. In this work, we propose a benchmark comprising various datasets, layout algorithms and their hyperparameters, and quality metrics for conducting an empirical study.

Abstract Various web-based image-editing tools and web-based collaborative tools exist in isolation. Research focusing to bridge the gap between these two domains is sparse. We respond to the above and develop prototype groupware for real-time collaborative editing of raster and vector images in a web browser. To better understand the requirements, we conduct a preliminary user study and establish communication and synchronization as key elements. The existing groupware for text documents or presentations handles the above through well-established techniques. However, those cannot be extended as it is for raster or vector graphics manipulation. To this end, we develop a document model that is maintained by a server and is delivered and synchronized to multiple clients. Our prototypical implementation is based on a scalable client–server architecture: using WebGL for interactive browser-based rendering and WebSocket connections to maintain synchronization. We evaluate our work qualitatively through a post-deployment user study for three different scenarios. For quantitative evaluation, we perform a thorough performance measure on both client and server side, thereby identifying design recommendations for future concurrent image-editing software(s).

Abstract Fast style transfer methods have recently gained popularity in art-related applications as they make a generalized real-time stylization of images practicable. However, they are mostly limited to one-shot stylizations concerning the interactive adjustment of style elements. In particular, the expressive control over stroke sizes or stroke orientations remains an open challenge. To this end, we propose a novel stroke-adjustable fast style transfer network that enables simultaneous control over the stroke size and intensity, and allows a wider range of expressive editing than current approaches by utilizing the scale-variance of convolutional neural networks. Furthermore, we introduce a network-agnostic approach for style-element editing by applying reversible input transformations that can adjust strokes in the stylized output. At this, stroke orientations can be adjusted, and warping-based effects can be applied to stylistic elements, such as swirls or waves. To demonstrate the real-world applicability of our approach, we present StyleTune, a mobile app for interactive editing of neural style transfers at multiple levels of control. Our app allows stroke adjustments on a global and local level. It furthermore implements an on-device patch-based upsampling step that enables users to achieve results with high output fidelity and resolutions of more than 20 megapixels. Our approach allows users to art-direct their creations and achieve results that are not possible with current style transfer applications.

Various web-based image-editing tools and web-based collaborative tools exist in isolation. Research focusing to bridge the gap between these two domains is sparse. We respond to the above and develop prototype groupware for real-time collaborative editing of raster images in a web browser. To better understand the requirements, we conduct a preliminary user study and establish communication and synchronization as key elements. The existing groupware for text documents, presentations, and vector graphics handles the above through well-established techniques. However, those cannot be extended as it is for raster graphics manipulation. To this end, we develop a document model that is maintained by a server and is delivered and synchronized to multiple clients. Our prototypical implementation is based on a scalable client-server architecture: using WebGL for interactive browser-based rendering and WebSocket connections to maintain synchronization. We evaluate our work qualitatively through a post-deployment user study for three different scenarios.

We present StyleTune, a mobile app for interactive multi-level control of neural style transfers that facilitates creative adjustments of style elements and enables high output fidelity. In contrast to current mobile neural style transfer apps, StyleTune supports users to adjust both the size and orientation of style elements, such as brushstrokes and texture patches, on a global as well as local level. To this end, we propose a novel stroke-adaptive feed-forward style transfer network, that enables control over stroke size and intensity and allows a larger range of edits than current approaches. For additional level-of-control, we propose a network-agnostic method for stroke-orientation adjustment by utilizing the rotation-variance of Convolutional Neural Networks (CNNs). To achieve high output fidelity, we further add a patch-based style transfer method that enables users to obtain output resolutions of more than 20 Megapixel (Mpix). Our approach empowers users to create many novel results that are not possible with current mobile neural style transfer apps.

This paper presents a service-based approach towards content moderation of digital visual media while browsing web pages. It enables the automatic analysis and classification of possibly offensive content, such as images of violence, nudity, or surgery, and applies common image abstraction techniques at different levels of abstraction to these to lower their affective impact. The system is implemented using a microservice architecture that is accessible via a browser extension, which can be installed in most modern web browsers. It can be used to facilitate content moderation of digital visual media such as digital images or to enable parental control for child protection.

Software visualization uses metaphors to depict software system and software development data that usually has no inherent gestalt. The choice of a fitting metaphor for visual display is researched broadly, but deriving a layout based on similarity is still challenging. We present a novel approach to 3D software visualization called Software Galaxy. Our layout is based on applying Latent Dirichlet Allocation on source code documents. We utilize a metaphor inspired from astronomy for depicting software metrics for single documents and clusters of documents. Our first experiments indicate that a 3D visualization capturing semantic relatedness can be beneficial for standard program comprehension tasks.

Personal, long-term investment products, especially ones for retirement savings, require thorough understanding to use them profitably. Even simple savings plans based on exchange-traded funds (ETFs) are subject to many variables and uncertainties to be considered for expected and planned-upon returns. We present an interactive simulation of an ETF-based savings plan that combines forecasts, risk awareness, taxes and costs, inflation, and dynamic inflows and outflows into a single visualization. The visualization consists of four parts: a form-fill interface for configuration, a savings and payout simulation, a cash flow chart, and a savings chart. Based on a specific use case, we discuss how private investors can benefit from using our visualization after a short training period.

This work investigates the extent to which animated procedural texture patterns can be used to support the representation of changes in 2.5D treemaps. Changes in height, color, and area of individual nodes can easily be visualized using animated transitions. Especially for changes in the color attribute, plain animated transitions are not able to directly communicate the direction of change itself. We show how procedural texture patterns can be superimposed to the color mapping and support transitions. To this end, we discuss qualitative properties of each pattern, demonstrate their ability to communicate change direction both with and without animation, and conclude which of the patterns are more likely to increase effectiveness and correctness of the change mapping in 2.5D treemaps.

Abstract Intrinsic decomposition refers to the problem of estimating scene characteristics, such as albedo and shading, when one view or multiple views of a scene are provided. The inverse problem setting, where multiple unknowns are solved given a single known pixel‐value, is highly under‐constrained. When provided with correlating image and depth data, intrinsic scene decomposition can be facilitated using depth‐based priors, which nowadays is easy to acquire with high‐end smartphones by utilizing their depth sensors. In this work, we present a system for intrinsic decomposition of RGB‐D images on smartphones and the algorithmic as well as design choices therein. Unlike state‐of‐the‐art methods that assume only diffuse reflectance, we consider both diffuse and specular pixels. For this purpose, we present a novel specularity extraction algorithm based on a multi‐scale intensity decomposition and chroma inpainting. At this, the diffuse component is further decomposed into albedo and shading components. We use an inertial proximal algorithm for non‐convex optimization (iPiano) to ensure albedo sparsity. Our GPU‐based visual processing is implemented on iOS via the Metal API and enables interactive performance on an iPhone 11 Pro. Further, a qualitative evaluation shows that we are able to obtain high‐quality outputs. Furthermore, our proposed approach for specularity removal outperforms state‐of‐the‐art approaches for real‐world images, while our albedo and shading layer decomposition is faster than the prior work at a comparable output quality. Manifold applications such as recoloring, retexturing, relighting, appearance editing, and stylization are shown, each using the intrinsic layers obtained with our method and/or the corresponding depth data.

Treemaps are a commonly used tool for the visual display and communication of tree-structured, multi-variate data. In order to confidently know when and how treemaps can best be applied, the research community uses usability studies and controlled experiments to "understand the potential and limitations of our tools" (Plaisant, 2004). To support the communities' understanding and usage of treemaps, this survey provides a comprehensive review and detailed overview of 69 user studies related to treemaps. However, due to pitfalls and shortcomings in design, conduct, and reporting of the user studies, there is little that can be reliably derived or accepted as a generalized statement. Fundamental open questions include configuration, compatible tasks, use cases, and perceptional characteristics of treemaps. The reliability of findings and statements is discussed and common pitfalls of treemap user studies are identified.

A truthful and unbiased display of data using information visualization requires detecting and communicating uncertainty. Uncertainty is often inherent in data or is introduced by data processing and visualization (e.g., visual display of accumulated data) but frequently not accounted for. This paper discusses the suitability of advanced visual variables such as sketchiness, noise, nesting-level contouring, and color weaving for communicating uncertainty.

This paper provides an overview of published treemap layout algorithms from 1991 to 2019 that were used for information visualization and computational geometry. First, a terminology is outlined for the precise communication of tree-structured data and layouting processes. Second, an overview and classification of layout algorithms is presented and application areas are discussed. Third, the use-case-specific adaption process is outlined and discussed. This overview targets practitioners and researchers by providing a starting point for own research, visualization design, and applications.

In this paper, we present a 2.5D visualization technique based on the dust & magnet metaphor, which generally allows for interactively exploring and analyzing large multivariate data sets. In addition to position and color, we introduce height as additional visual variable for particles to encode extra data attributes in the 2.5D visualization, thus increasing the potential for identifying correlations between attributes. Further, we have developed a real-time collision detection algorithm as part of the particle simulation that ensures overlap-free particle positioning, thereby enabling the continuous perception of patterns, clusters, and outliers. These extensions facilitate on-the-fly validation of hypotheses through the highly dynamic configuration of magnets and visual attribute encoding, which also allows for a better integration of the user's domain knowledge.

The availability of detailed virtual 3D building models including representations of indoor elements, allows for a wide number of applications requiring effective exploration and navigation functionality. Depending on the application context, users should be enabled to focus on specific Objects-of-Interests (OOIs) or important building elements. This requires approaches to filtering building parts as well as techniques to visualize important building objects and their relations. For it, this paper explores the application and combination of interactive rendering techniques as well as their semantically-driven configuration in the context of 3D indoor models.

This paper presents an interactive rendering technique for detail+overview visualization of 3D digital terrain models using interactive close-ups. A close-up is an alternative presentation of input data varying with respect to geometrical scale, mapping, appearance, as well as Level-of-Detail (LOD) and Level-of-Abstraction (LOA) used. The presented 3D closeup approach enables in-situ comparison of multiple Region-of-Interests (ROIs) simultaneously. We describe a GPU-based rendering technique for the image-synthesis of multiple closeups in real-time.

A fundamental task in 3D geovisualization and GIS applications is the visualization of vector data that can represent features such as transportation networks or land use coverage. Mapping or draping vector data represented by geometric primitives (e.g., polylines or polygons) to 3D digital elevation or 3D digital terrain models is a challenging task. We present an interactive GPU-based approach that performs geometry-based draping of vector data on per-frame basis using an image-based representation of a 3D digital elevation or terrain model only.

Software maps provide a general-purpose interactive user interface and information display for software analytics tools. This paper systematically introduces and classifies software maps as a treemap-based technique for software cartography. It provides an overview of advanced visual metaphors and techniques, each suitable for interactive visual analytics tasks, that can be used to enhance the expressiveness of software maps. Thereto, the metaphors and techniques are briefly described, located within a visualization pipeline model, and considered within the software map design space. Consequent applications and use cases w.r.t. different types of software system data and software engineering data are discussed, arguing for a versatile use of software maps in visual software analytics.

Mobility analytics is a growing field with various use-cases. Specific tools for visual, spatial, and spatio-temporal analysis are not only important for trained professionals and experts of GIS, but also required by non-domain experts, such as urban planners, business managers, and private users. In this paper, a web-based visualization technique for mobility analysis using reachability maps of multimodal transportation networks is presented.

Transportation networks are important components of digital maps. The display of streets and railroad lines are a key for orientation and navigation using traditional and digital maps. While 2D digital maps enable effective communication, their visualization within 3D digital maps, based on virtual 3D city models, is often subject to occlusion that hinders the effective perception. There are a number of approaches to partially resolve occlusion effects within 3D geovirtual environments such as ghosted and cut-away views as well as interactive multi-perspective views are often applied. This paper proposes occlusion hints to emphasize occluded parts of transportation networks. In contrast to existing occlusion management techniques, these present only hints towards occluded parts to the viewer.

Mobile expressive rendering gained increasing popularity among users seeking casual creativity by image stylization and supports the development of mobile artists as a new user group. In particular, neural style transfer has advanced as a core technology to emulate characteristics of manifold artistic styles. However, when it comes to creative expression, the technology still faces inherent limitations in providing low-level controls for localized image stylization. This work enhances state-of-the-art neural style transfer techniques by a generalized user interface with interactive tools to facilitate a creative and localized editing process. Thereby, we first propose a problem characterization representing trade-offs between visual quality, run-time performance, and user control. We then present MaeSTrO, a mobile app for orchestration of neural style transfer techniques using iterative, multi-style generative and adaptive neural networks that can be locally controlled by on-screen painting metaphors. At this, first user tests indicate different levels of satisfaction for the implemented techniques and interaction design.

Today's rendering APIs lack robust functionality and capabilities for dynamic, real-time text rendering and labeling, which represent key requirements for 3D application design in many fields. As a consequence, most rendering systems are barely or not at all equipped with respective capabilities. This paper drafts the unified text rendering and labeling API OpenLL intended to complement common rendering APIs, frameworks, and transmission formats. For it, various uses of static and dynamic placement of labels are showcased and a text interaction technique is presented. Furthermore, API design constraints with respect to state-of-the-art text rendering techniques are discussed. This contribution is intended to initiate a community-driven specification of a free and open label library.

The 2.5D treemap facilitates interactive exploration of multivariate data. It includes height as a visual variable for additional information display and enables exploration of correlations within mapped attributes. In this paper techniques for the visual display of a height reference for interactive modification from within the visualization are introduced. Results of a preliminary user study are presented and potential benefits for improved performance, i.e., precision and speed, of identification, comparison, filtering, and selection tasks are discussed.

This paper presents a novel technique for combining 2D and 2.5D treemaps using multi-perspective views to leverage the advantages of both treemap types. It enables a new form of overview+detail visualization for tree-structured data and contributes new concepts for real-time rendering of and interaction with treemaps. The technique operates by tilting the graphical elements representing inner nodes using affine transformations and animated state transitions. We explain how to mix orthogonal and perspective projections within a single treemap. Finally, we show application examples that benefit from the reduced interaction overhead.

Treemaps serve as generic, effective tools to display, explore, and analyze multi-variate tree data in a scalable, interactive, and consistent way. In this paper, we discuss and evaluate sketchiness as visual variable of 2.5D treemaps. Sketchy rendering techniques allow us to map data, e.g., about uncertainty, imprecision, or vagueness, independently from mappings to other visual variables such as size, color, and height. To this end, we present a design space for sketchy rendering for 2.5D treemaps and corresponding implementation of a real-time sketchy rendering technique. The results of three user studies carried out indicate that sketchiness is a promising candidate for an independent visual variable for 2.5D treemaps, in particular to map ordinal data with a small range such as data that qualifies map items, it shows no strong interference with other visual variables such as color and height due to the regular gestalt of blocks and, hence, allows us to extend the expressiveness of 2.5D treemaps.

Hybrid terrain models combine large regular data sets and high-resolution irregular meshes [triangulated irregular network (TIN)] for topographically and morphologically complex terrain features such as man-made microstructures or cliffs. In this paper, a new method to generate and visualize this kind of 3D hybrid terrain models is presented. This method can integrate geographic data sets from multiple sources without a remeshing process to combine the heterogeneous data of the different models. At the same time, the original data sets are preserved without modification, and, thus, TIN meshes can be easily edited and replaced, among other features. Specifically, our approach is based on the utilization of the external edges of convexified TINs as the fundamental primitive to tessellate the space between both types of meshes. Our proposal is eminently parallel, requires only a minimal preprocessing phase, and minimizes the storage requirements when compared with the previous proposals.

This paper presents a novel visualization technique for the interactive exploration of multi-threaded software systems. It combines the visualization of static system structure based on the Evo Streets approach with an additional traffic metaphor to communicate the runtime characteristics of multiple threads simultaneously. To improve visual scalability with respect to the visualization of complex software systems, we further present an effective level-of-detail visualization based on hierarchical aggregation of system components by taking viewing parameters into account. We demonstrate our technique by means of a prototypical implementation and compare our result with existing visualization techniques.

With increasing numbers of flights world-wide and a continuing rise in airport traffic, air-traffic management is faced with a number of challenges. These include monitoring, reporting, planning, and problem analysis of past and current air traffic, e.g., To identify hotspots, minimize delays, or to optimize sector assignments to air-traffic controllers. Interactive and dynamic 3D visualization and visual analysis of massive aircraft trajectories, i.e., Analytical reasoning enabled by interactive cyber worlds, can be used to approach these challenges. To facilitate this kind of analysis, especially in the context of real-time data, interactive tools for filtering, mapping, and rendering are required. In particular, the mapping process should be configurable at run-time and support both static mappings and animations to allow users to effectively explore and realize movement dynamics. However, with growing data size and complexity, these stages of the visualization pipeline require computational efficient implementations to be capable of processing within real-time constraints. This paper presents an approach for real-time animated visualization of massive air-traffic data, that implements all stages of the visualization pipeline based on GPU techniques for efficient processing. It enables (1) interactive spatio-temporal filtering, (2) generic mapping of trajectory attributes to geometric representations and appearances, as well as (3) real-time rendering within 3D virtual environments, such as virtual 3D airport and city models. Based on this pipeline, different visualization metaphors (e.g., Temporal focus context, density maps, and overview detail visualization) are implemented and discussed. The presented concepts and implementation can be generally used as visual analytics and data mining techniques in cyber worlds, e.g., To visualize movement data, geo-referenced networks, or other spatio-temporal data.

This article presents multi-perspective 3D panoramas that focus on visualizing 3D geovirtual environments (3D GeoVEs) for navigation and exploration tasks. Their key element, a multi-perspective view (MPV), seamlessly combines what is seen from multiple viewpoints into a single image. This approach facilitates the presentation of information for virtual 3D city and landscape models, particularly by reducing occlusions, increasing screen-space utilization, and providing additional context within a single image. We complement MPVs with cartographic visualization techniques to stylize features according to their semantics and highlight important or prioritized information. When combined, both techniques constitute the core implementation of interactive, multi-perspective 3D panoramas. They offer a large number of effective means for visual communication of 3D spatial information, a high degree of customization with respect to cartographic design, and manifold applications in different domains. We discuss design decisions of 3D panoramas for the exploration of and navigation in 3D GeoVEs. We also discuss a preliminary user study that indicates that 3D panoramas are a promising approach for navigation systems using 3D GeoVEs.

Understanding the execution of programs by means of program traces is a key strategy in software comprehension. An important task in this context is comparing two traces in order to find similarities and differences in terms of executed code, execution order, and execution duration. For large and complex program traces, this is a difficult task due to the cardinality of the trace data. In this paper, we propose a new visualization method based on icicle plots and edge bundles. We address visual scalability by several multiscale visualization metaphors, which help users navigating from the main differences between two traces to intermediate structural-difference levels, and, finally fine-grained function call levels. We show how our approach, implemented in a tool called TRACEDIFF, is applicable in several scenarios for trace difference comprehension on real-world trace datasets.

In software comprehension, program traces are important to gain insight into certain aspects of concurrent runtime behavior, e.g., thread-interplay. Here, key tasks are finding usages of blocking operations, such as synchronization and I/O operations, assessing temporal order of such operations, and analyzing their effects. This is a hard task for large and complex program traces due to their size and number of threads involved. In this paper, we present SYNCTRACE a new visualization technique based on (bended) activity diagrams and edge bundles that allows for parallel analysis of multiple threads and their inter-thread correspondences. We demonstrate how the technique, implemented as a tool, can be applied on real-world trace datasets to support understanding concurrent behavior.

Ensuring code quality represents an essential task in "perfective software maintenance", which aims at keeping future maintenance costs low by facilitating adaptations of complex software systems. For this purpose, changes and related efforts have to be identified that imply high positive impact on future maintainability. In this paper, we propose a novel assessment method that applies visual analysis techniques to combine multiple indicators for low maintainability, including code complexity and entanglement with other parts of the system, and recent changes applied to the code. The approach generally helps to identify modules that impose a high risk by causing increased future maintenance efforts. Consequently, it allows for exploration, analysis, and planning of different preventive measures that, e.g., most likely will have a high return on investment. In our tool implementation, we use circular bundle views, extended by the third dimension in which indicators can be mapped to. We have evaluated our approach by conducting a case study based on our tool for a large-scale software system of an industry partner.

Abstract Virtual 3D city models play an important role in the communication of complex geospatial information in a growing number of applications, such as urban planning, navigation, tourist information, and disaster management. In general, homogeneous graphic styles are used for visualization. For instance, photorealism is suitable for detailed presentations, and non‐photorealism or abstract stylization is used to facilitate guidance of a viewer's gaze to prioritized information. However, to adapt visualization to different contexts and contents and to support saliency‐guided visualization based on user interaction or dynamically changing thematic information, a combination of different graphic styles is necessary. Design and implementation of such combined graphic styles pose a number of challenges, specifically from the perspective of real‐time 3D visualization. In this paper, the authors present a concept and an implementation of a system that enables different presentation styles, their seamless integration within a single view, and parametrized transitions between them, which are defined according to tasks, camera view, and image resolution. The paper outlines potential usage scenarios and application fields together with a performance evaluation of the implementation.

Hybrid terrains are a convenient approach for the representation of digital terrain models, integrating heterogeneous data from different sources. In this article, we present a general, efficient scheme for achieving interactive level-of-detail rendering of hybrid terrain models, without the need for a costly preprocessing or resampling of the original data. The presented method works with hybrid digital terrains combining regular grid data and local high-resolution triangulated irregular networks. Since grid and triangulated irregular network data may belong to different datasets, a straightforward combination of both geometries would lead to meshes with holes and overlapping triangles. Our method generates a single multiresolution model integrating the different parts in a coherent way, by performing an adaptive tessellation of the region between their boundaries. Hence, our solution is one of the few existing approaches for integrating different multiresolution algorithms within the same terrain model, achieving a simple interactive rendering of complex hybrid terrains.

To understand software systems it is common practice to explore runtime information such as method calls. System behavior analysis can further be facilitated by additionally taking runtime data dependencies into account. In object oriented systems, a typical data dependency is the information about which objects are accessed by the traced method calls. To support software engineers in handling the massive amount of information that execution traces typically consist of, highly scalable visualizations are needed. In this paper, we propose a trace-visualization technique that (a) explicitly visualizes both, method calls and object accesses, and (b) provides high scalability to handle large execution traces. With regard to the visualization technique proposed, we give a systematic overview of visual patterns that are to be expected and of their meanings with respect to system behavior. Additionally, we present the results of three case-studies to show how our approach facilitates developers in comprehending the behavior of complex C++ software systems.

Interactive 3D geovirtual environments (GeoVE), such as 3D virtual city and landscape models, are important tools to communicate geo-spatial information. Usually, this includes static polygonal data (e.g., digital terrain model) and raster data (e.g., aerial images) which are composed from multiple data sources during a complex, only partial automatic pre-processing step. When dealing with highly dynamic geo-referenced raster data, such as the propagation of fires or floods, this pre-processing step hinders the direct application of 3D GeoVE for decision support systems. To compensate for this limitation, this paper presents a concept for dynamically mapping multiple layers of raster for interactive GeoVE. The implementation of our rendering technique is based on the concept of projective texture mapping and can be implemented efficiently using consumer graphics hardware. Further, this paper demonstrates the flexibility of our technique using a number of typical application examples.

Indoor routing represents an essential feature required by applications and systems that provide spatial information about complex sites, buildings and infrastructures such as in the case of visitor guidance for trade fairs and customer navigation at airports or train stations. Apart from up-to date, precise 3D spatial models these systems and applications need user interfaces as core system components that allow users to efficiently express navigation goals and to effectively visualize routing information. For interoperable and flexible indoor routing systems, common specifications and standards for indoor structures, objects, and relationships are needed as well as for metadata such as data quality and certainty. In this paper, we introduce a classification of indoor objects and structures taking into account geometry, semantics, and appearance, and propose a level-of-detail model for them that supports the generation of effective indoor route visualization.

Abstract We present a non‐photorealistic rendering technique to transform color images and videos into painterly abstractions. It is based on a generalization of the Kuwahara filter that is adapted to the local shape of features, derived from the smoothed structure tensor. Contrary to conventional edge‐preserving filters, our filter generates a painting‐like flattening effect along the local feature directions while preserving shape boundaries. As opposed to conventional painting algorithms, it produces temporally coherent video abstraction without extra processing. The GPU implementation of our method processes video in real‐time. The results have the clearness of cartoon illustrations but also exhibit directional information as found in oil paintings.

Focus + context visualization facilitates the exploration of complex information spaces. This paper proposes 3D generalization lenses, a new visualization technique for virtual 3D city models that combines different levels of structural abstraction. In an automatic preprocessing step, we derive a generalized representation of a given city model. At runtime, this representation is combined with a full-detail representation within a single view based on one or more 3D lenses of arbitrary shape. Focus areas within lens volumes are shown in full detail while excluding less important details of the surrounding area. Our technique supports simultaneous use of multiple lenses associated with different abstraction levels, can handle overlapping and nested lenses, and provides interactive lens modification.

Extending or modifying features of complex software systems is often a highly time-consuming and cost-intensive task as, beforehand, the features have to be located within the code and to be understood in detail. To support developers in performing this task, we propose a technique that takes execution traces and implementation unit structuring as input data and provides various views thereupon. Views focus on different trace characteristics, namely they are time-, collaboration-, and code-focused. Synchronizing the views creates a rich user interface that helps developers to effectively identify and understand feature relevant parts of the implementation.

In this paper, we present a technique that generalizes 3D building groups of virtual 3D city models according to a cell structure that is derived from infrastructure networks. In addition, the technique handles vegetation areas and outliers such as landmark buildings. Generalized 3D representations abstract from complex, detailed 3D city models and enable storage, analysis, exploration, and interaction at varying levels of scales. Our technique implements the cartographic generalization operators clustering, aggregation, and accentuation; it performs the generalization in four steps: 1) City model components are clustered based on the cell structure. 2) For each cell, the weighted average height is calculated, which is also used to automatically identify outliers. 3) Free space is subtracted from the cells such as in the case of outliers or vegetation areas. 4) The modified cells are extruded to building blocks; vegetation areas and outliers are modeled or, respectively, integrated separately. The paper demonstrates the application of the presented technique by a case study.

This paper presents an approach to visualize and analyze 3D building information models within virtual 3D city models. Building information models (BIMs) formalize and represent detailed information related to the lifecycle of buildings, e.g., information about composition, facilities, equipment, usage, maintenance, and workflows such as rescue scenarios. Complementary, virtual 3D city models represent objects and phenomena of urban areas, typically at a lower level of information detail; virtual 3D city models as a general framework and platform for spatial data allow us to seamlessly combine GIS and BIM data. In our approach, BIM data and 3D geodata, both provided by possibly distributed, heterogeneous web services, are efficiently integrated by the underlying real-time 3D geovisualization system. To facilitate insights into complex spatial scenarios, two configurable BIM-specific visualization techniques have been developed, which map BIM data onto 3D building graphics variables respectively geometrically distort 3D building representations. The visualization functionality can itself be accessed as a specialized web 3D perspective view service. We demonstrate our approach by a fire and rescue scenario for a part of a 3D campus model.

communicate visual ideas and can be used to present and reconsider drafts and concepts in product design. This paper introduces a real-time illustration technique that sketches the design and spatial assembly of CSG models. The illustration technique generates a graphical decomposition of the CSG model into disjunctive layers to extract 1) the perceptually important edges that outline the model’s outer and inner features and 2) the surface shading of the outer and inner faces. Then, the technique applies uncertainty to these layers to simulate a sketchy effect. Finally, the technique composes the sketched layers in depth-sorted order while ensuring a correct depth behavior in the frame buffer. Because the sketchy illustrations are frame-to-frame coherent, the technique can be used as a tool for interactive presentation and reconsideration of the design and spatial assembly of CSG models.

This paper describes an approach for smart and physically-based navigation, which aims at supporting effective and intuitive user interactions with 3D geovirtual environments (GeoVEs). The approach is based on two aligned concepts: 1) All navigation techniques are controlled by constraints that ensure user orientation and avoid "getting lost" situations. 2) All navigation techniques are handled in a time-coherent way achieving steady, continuous user movements using a physically-based motion model. Based on these concepts, we demonstrate several ways to improve commonly used navigation techniques for geovirtual environments.

Real-time rendering of massively textured 3D scenes usually involves two major problems: Large numbers of texture switches are a well-known performance bottleneck and the set of simultaneously visible textures is limited by the graphics memory. This paper presents a level-of-detail texturing technique that overcomes both problems. In a preprocessing step, the technique creates a hierarchical data structure for all textures used by scene objects, and it derives texture atlases at different resolutions. At runtime, our texturing technique requires only a small set of these texture atlases, which represent scene textures in an appropriate size depending on the current camera position and screen resolution. Independent of the number and total size of all simultaneously visible textures, the achieved frame rates are similar to that of rendering the scene without any texture switches. Since the approach includes dynamic texture loading, the total size of the textures is only limited by the hard disk capacity. The technique is applicable for any 3D scenes whose scene objects are primarily distributed in a plane, such as in the case of 3D city models or outdoor scenes in computer games. Our approach has been successfully applied to massively textured, large-scale 3D city models.

For visual perception of 3D models, shading plays one of the major roles. The shading quality of level-of-detail models is limited generally because existing LOD algorithms assume a conceptually smooth surface. A complex mesh, however, is likely to have conceptually smooth and angular parts. We introduce an extension to the progressive mesh LOD approach that efficiently handles triangle meshes with large numbers of shading discontinuities. For this, the algorithm distinguishes three principal shading situations for mesh vertices: completely continuous shading, completely discontinuous shading, and mixed continuous/discontinuous shading. Remarkably, the algorithm does not introduce any overhead for completely smooth surfaces. As one field of application, we briefly outline its application for LOD representations of 3D city models.

City models have become central elements for visually communicating spatial information related to urban areas and have manifold applications. Our real-time nonphotorealistic rendering technique aims at abstract, comprehensible, and vivid drawings of assemblies of polygonal 3D urban objects. It takes into account related principles in cartography, cognition, and nonphotorealism. Technically, the geometry of a building is rendered using expressive line drawings to enhance the edges, two-tone or three-tone shading to draw the faces, and simulated shadows. The edge enhancement offers several degrees of freedom, such as interactively changing the style, width, tilt, color, transparency, and length of the strokes. Traditional drawings of cities and panoramas inspired the tone shading that achieves a pleasing visual color effect. The rendering technique can be applied not only to city models but to polygonal shapes in general.

No abstract available.

Describes the software architecture of a rendering system that follows a pragmatic approach to integrating and bundling the power of different low-level rendering systems within an object-oriented framework. The generic rendering system provides higher-level abstractions to existing rendering systems and serves as a framework for developing new rendering techniques. It wraps the functionality of several widely-used rendering systems, defines a unified object-oriented application programming interface and provides an extensible, customizable apparatus for evaluating and interpreting hierarchical scene information. As a fundamental property, individual features of a specific rendering system can be integrated into the generic rending system in a transparent way. The system is based on a state machine, called an "engine", which operates on "rendering components". Four major categories of rendering components constitute the generic rendering system: "shapes" represent geometries, "attributes" specify properties assigned to geometries and scenes, "handlers" encapsulate rendering algorithms, and "techniques" represent evaluation strategies for rendering components. As a proof of concept, we have implemented the described software architecture using the Virtual Rendering System, which currently wraps the functionality of the OpenGL, Radiance, POV Ray and RenderMan systems.

Three-dimensional maps are fundamental tools for presenting, exploring, and manipulating geo data. This paper describes multiresolution concepts for 3D maps and their texture-based design. In our approach, 3D maps are based on a hybrid, multiresolution terrain model composed of data sets having different topological structure, for example a coarse regular grid combined with by triangulated microstructure. Any number of texture layers can be associated with the terrain model. For each texture layer, the multiresolution structure builds a texture tree which is linked to geometry patches of the multiresolution terrain model. The terrain model together with multiple texture layers can be rendered in real-time, in particular if multitexturing is available. Texture layers can be combined by high-level operations such us blending and masking and can be rebuilt at run-time. This mechanism simplifies the implementation of visual exploration tools and of procedural, automated map designs. 3D maps facilitate the visual simulation of environmental issues in spatial support systems, virtual reality applications, real-time GIS, and interactive cartography.

Presents a new rendering technique for processing multiple multi-resolution textures of LOD (level-of-detail) terrain models and describes its application to interactive, animated terrain content design. The approach is based on a multi-resolution model for terrain texture which cooperates with a multi-resolution model for terrain geometry. For each texture layer, an image pyramid and a texture tree are constructed. Multiple texture layers can be associated with one terrain model and can be combined in different ways, e.g. by blending and masking. The rendering algorithm simultaneously traverses the multi-resolution geometry model and the multi-resolution texture model, and takes into account geometric and texture approximation errors. It uses multi-pass rendering and exploits multi-texturing to achieve real-time performance. Applications include interactive texture lenses, texture animation and topographic textures. These techniques offer an enormous potential for developing new visualization applications for presenting, exploring and manipulating spatio-temporal data.

The approximation tree is a hybrid, hierarchical data structure for real-time terrain visualization which represents both geometry data and texture data of a terrain in a hierarchical manner. This framework can integrate different multiresolution modeling techniques operating on different types of data sets such as TLNs, regular grids, and non-regular grids. An approximation tree recursively aggregates terrain patches which reference geometry data and texture data. The rendering algorithm selects patches based on a geometric approximation error and a texture approximation error. Terrain shading and thematic texturing, which can be generated in a preprocessing step, improve the visual quality of level of detail models and eliminate the defects resulting from a Gouraud shaded geometric model since they do not depend on the current (probably reduced) geometry. The approximation tree can be implemented efficiently using object-oriented design principles. A case study for cartographic landscape visualization illustrates the use of approximation trees.

If 3D applications become large, hierarchical networks of geometric objects lead to messy specifications. Furthermore, if time- and event-dependencies are merged with geometric modeling, complex animations and interactions cannot be modeled independently and hierarchically since their specifications are dispersed throughout the static scene description. The authors present an object-oriented architecture for interactive, animated 3D widgets which reduces the complexity of building 3D applications. 3D widgets encapsulate geometry and behavior into high-level building blocks based on two types of directed acyclic graphs, geometry graphs and behavior graphs. 3D widgets construct internal geometry graphs and behavior graphs, and perform operations on these graphs through high-level interfaces which hide details and raise the level of abstraction. 3D widgets define object ports which are used to link together different 3D widgets. A visual language for 3D widgets allows the developer the interactive construction of 3D applications.

Article Free Access Share on An interactive environment for visualizing and animating algorithms Authors: Júrgen Döllner FB 15, Institut für Informatik, Westfälische Wilhelms-Universität, Einsteinstr. 62, D - 48149 Münster, Germany FB 15, Institut für Informatik, Westfälische Wilhelms-Universität, Einsteinstr. 62, D - 48149 Münster, GermanyView Profile , Klaus Hinrichs FB 15, Institut für Informatik, Westfälische Wilhelms-Universität, Einsteinstr. 62, D - 48149 Münster, Germany FB 15, Institut für Informatik, Westfälische Wilhelms-Universität, Einsteinstr. 62, D - 48149 Münster, GermanyView Profile , Hermann Spiegel FB 15, Institut für Informatik, Westfälische Wilhelms-Universität, Einsteinstr. 62, D - 48149 Münster, Germany FB 15, Institut für Informatik, Westfälische Wilhelms-Universität, Einsteinstr. 62, D - 48149 Münster, GermanyView Profile Authors Info & Claims SCG '97: Proceedings of the thirteenth annual symposium on Computational geometryAugust 1997 Pages 409–411https://doi.org/10.1145/262839.263032Published:01 August 1997Publication History 0citation294DownloadsMetricsTotal Citations0Total Downloads294Last 12 Months4Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

We present an object-oriented 3D graphics and animation framework which provides a new methodology for the symmetric modelling of geometry and behaviour. The toolkit separates the specification of geometry and behaviour by two types of directed acyclic graphs, the geometry graph and the behaviour graph, which are linked together through constraint relations. All geometry objects and behaviour objects are represented as DAG nodes. The geometry graph provides a renderer-independent hierarchical description of 3D scenes and rendering processes. The behaviour graph specifies time- and event-dependent constraints applied to graphics objects. Behaviour graphs simplify the specification of complex animations and 3D interactions by providing nodes for the management of the time and event flow (e.g. durations, time layouts, time repeaters, actions). Nodes contain, manipulate and share instances of constrainable graphical abstract data types. Geometry nodes and behaviour nodes are used to configure high-level 3D widgets, i.e. high-level building blocks for constructing 3D applications. The fine-grained object structure of the system leads to an extensible reusable framework which can be implemented efficiently. © 1997 by John Wiley & Sons, Ltd.