Mixed Reality (MR) interfaces have traditionally relied on visual modalities, but this poses challenges in high-stakes or cognitively demanding contexts where continuous visual attention is impractical. This exploratory study investigates audio-centric interaction in MR, specifically focusing on 3D spatial navigation. Unlike prior work limited to 2D navigation, we developed a custom augmented reality (AR) navigation system to compare audio AR (AAR) with (1) visual AR, (2) combined audio-visual AR, and (3) traditional navigation without aids. Results show that AAR enables users to maintain environmental awareness comparable to those without AR assistance, while showing no meaningful difference in navigation performance with visual AR in complex 3D environments. Qualitative reports and awareness tests suggest AAR reduces visual tunneling. These exploratory findings suggest the potential use of AAR in many surrounding fields, such as accessibility for blind or visually impaired individuals or training resources for first responders, offering insights into audio interface design for safety-critical applications.

The importance of location for business success cannot be overstated. Existing approaches to the business location selection problem often involve creating extensively tuned models specific to the geographical and economic climate being analyzed, making them difficult to adapt to other scenarios. This poses a significant challenge in regions where data are scarce or costly to obtain. In this article, we experiment with various offline deep Q-learning (DQL) frameworks for business location recommendation that can be trained in one geographic area and applied to another without requiring further training or tuning. Our comprehensive experiments on real-world data demonstrate the superior generalizability of our DQL approaches, outperforming the well-established Huff gravity model by more than 25% in profit realization on average across all DQN variants and business categories, with an average profit realization of 75.35%. Our results indicate that the variation in the training data must be as high as the variation in the test data for the model to be successfully applied to other locations, despite discrepancies between the characteristics of the cities. Our approach offers a highly generalizable and easily applicable solution to the business location selection problem, providing a strong alternative to gravity-based models in settings with limited access to localized data.

ABSTRACT As Extended Reality (XR) technologies continue gaining popularity, various domains seek to integrate them into their workflows to enhance performance and user satisfaction. However, integrating XR technologies into emergency response presents unique challenges. Unlike other fields, such as healthcare, entertainment, or education, emergency response involves physically demanding environments and information‐intensive tasks that first responders (FRs) must perform. Augmented reality (AR) head‐mounted displays (HMDs) present promising solutions for improving situational awareness and reducing the cognitive load of the FRs. However, limited research has focused on the specific needs of FRs. Moreover, existing studies investigating FR needs have primarily been conducted in controlled laboratory settings, revealing a significant gap in the literature concerning FR requirements in real‐life scenarios. This work addresses this gap through a comprehensive user study with subject matter experts (SMEs) and FRs. User studies were conducted after two different real‐life scenarios using AR HMDs. To further understand FR needs, we extensively reviewed the literature for similar studies that reported FR needs, explicitly focusing on studies including interviews with SMEs and FRs. Our findings identified key design guidelines for FR‐friendly AR interfaces while also highlighting the direction for future research to improve the user experience of the FRs.

Abstract Comic inpainting is essential for language localization and adapting comics into animations, involving the removal of speech boxes, textboxes, and sound effects while maintaining artistic integrity. This paper introduces an automated approach leveraging the Manga inpainting method by Xie et al., adapted for western comics like Tex Willer. Tex Willer comics, known for their fusion of Italian art and American Western imagery, pose unique challenges due to their distinct styles. Customized Manga Restoration and Structural Line Extraction codes are employed, along with automated mask generation using deep CNN-based speech balloon detection and segmentation. Our contributions include the development of a precise model tailored to Tex Willer Comics, resulting in visually coherent inpainting results. The paper follows a structured format, covering State-of-the-Art, methodology, results, and conclusions, aiming to streamline the process of western comic inpainting for professionals in the comics and animation industries.

In an exploratory investigation into interface preferences among first responders, this study examines the usability of mobile and augmented reality (AR) interfaces among a mixed group of firefighters and paramedics. While prior studies predominantly assessed XR interfaces for civilian and single-domain user groups, this research is novel in its comparative analysis of two distinct professional groups. Through a combination of a 20-question survey and expert interviews, findings reveal a general preference for mobile interfaces over AR. Notably, firefighters highlighted the potential of AR when integrated into their protective gear, while paramedics leaned towards the practicality of mobile interfaces. This nuanced understanding of user needs underscores the importance of tailored technology solutions in emergency services.

Whenever companies plan to enter new geographical areas, they need disaggregated sales in each location. To make such predictions, sales time series or final customers' data in geographical disaggregation are necessary. However, for most companies, such datasets are unavailable or impractical. The manuscript has two main goals. One focal problem is how to disaggregate an aggregate sales prediction with no historical proportions. The other is how to improve spatial models using Point of Interest (POI) data. To solve these problems, we combine two literature streams — spatial marketing and sales forecasting — and propose a new hybrid probabilistic approach: Gravitational Sales Prediction (GSP). Our approach uses POI data to estimate area attraction, customer stocks, and flows to predict sales proportions. We later use these proportions to disaggregate an aggregate forecast. GSP is validated using sales data from two countries and more than ten economic segments. When compared to a strong benchmark that relies on past sales proportions, GSP exceeded expectations by achieving not only a similar performance to the benchmark but also outperforming it in some locations. It showed the most promising results in the middle level of aggregation. The result is a powerful and flexible approach that can be embedded in any decision support system.

In interactive data analysis processes, the dialogue between the human and the computer is the enabling mechanism that can lead to actionable observations about the phenomena being investigated. It is of paramount importance that this dialogue is not interrupted by slow computational mechanisms that do not consider any known temporal human-computer interaction characteristics that prioritize the perceptual and cognitive capabilities of the users. In cases where the analysis involves an integrated computational method, for instance to reduce the dimensionality of the data or to perform clustering, such non-optimal processes are often likely. To remedy this, progressive computations, where results are iteratively improved, are getting increasing interest in visual analytics. In this paper, we present techniques and design considerations to incorporate progressive methods within interactive analysis processes that involve high-dimensional data. We define methodologies to facilitate processes that adhere to the perceptual characteristics of users and describe how online algorithms can be incorporated within these. A set of design recommendations and according methods to support analysts in accomplishing high-dimensional data analysis tasks are then presented. Our arguments and decisions here are informed by observations gathered over a series of analysis sessions with analysts from finance. We document observations and recommendations from this study and present evidence on how our approach contribute to the efficiency and productivity of interactive visual analysis sessions involving high-dimensional data.

Light source estimation and virtual lighting must be believable in terms of appearance and correctness in augmented reality scenes. As a result of illumination complexity in an outdoor scene, realistic lighting for augmented reality is still a challenging problem. In this paper, we propose a framework based on an estimation of environmental lighting from well-defined objects, specifically human faces. The method is tuned for outdoor use, and the algorithm is further enhanced to illuminate virtual objects exposed to direct sunlight. Our model can be integrated into existing mobile augmented reality frameworks to enhance visual perception.

We propose a novel multi-view visualization technique, which allows effortless interaction with subterranean data and tries to maximize spatial perception whilst minimizing view clutter. The multi-view augmented reality technique introduces two correlating displays; i) a perspective egocentric view with focused edge overlay and focused geometry clipping and ii) an orthographic cut-away display that visualizes a thin slice of subterranean data intersecting a user controlled anchor.

ABSTRACT We propose a new method based on the use of fractional differentiation for improving the efficiency and realism of simulations based on smoothed particle hydrodynamics (SPH). SPH represents a popular particle‐based approach for fluid simulation and a high number of particles is typically needed for achieving high quality results. However, as the number of simulated particles increase, the speed of computation degrades accordingly. The proposed method employs fractional differentiation to improve the results obtained with SPH in a given resolution. The approach is based on the observation that effects requiring a high number of particles are most often produced from colliding flows, and therefore, when the modeling of this behavior is improved, higher quality results can be achieved without changing the number of particles being simulated. Our method can be employed to reduce the resolution without significant loss of quality, or to improve the quality of the simulation in the current chosen resolution. The advantages of our method are demonstrated with several quantitative evaluations. Copyright © 2013 John Wiley & Sons, Ltd.

This special issue contains 28 papers selected from the Computer Animation and Social Agents 2013 (CASA'2013) Conference. This conference was founded by the Computer Graphics Society in 1988 in Geneva and has, since then, been held in various countries around the world, 2011 in China, last year in Singapore, this year in Istanbul, Turkey, and next year in Houston, USA. The 3-day conference features more than 55 speakers who present their most current research in the areas of computer animation, autonomous social robots and virtual humans, and how these technologies can be leveraged to advance related areas, such as music, virtual cities, and crowd control. Addressing this year's conference are human motion modeling expert associate professor Jinxiang Chai from Texas A&M University and renowned haptics researcher, associate professor Cagatay Basdogan of Koc University. This year, we received 141 full papers and selected only 28 of those for this special issue; meaning, an acceptance rate of only 20%. It is needless to say that these are of high quality, all having been reviewed by at least three reviewers. The themes are various, covering the entire international field of research in computer animation and virtual worlds and sorted by their sessions in the conference; they are as follows. Crowd Simulation, Fluid Simulation, Natural Phenomena and Lighting, Face/Hair Animation and Rendering, Virtual Cities and Path Planning, Paint Simulation, Medical/Immersive Applications, Virtual Agents, 3D Mesh Deformation, Human Action Recognition, 3D Mesh and Geometric Modeling, and Human Motion. We would like to thank the authors for having submitted a paper to CASA'2013 as well as the Program Committee members, the external reviewers, and all the people who have contributed to the success of CASA 2013 in Istanbul. Nadia Magnenat-Thalmann Mustafa Kasap Daniel Thalmann Tolga Capin Selim Balcisoy Tolga Eren Norman Badler Selim Balcisoy Ronan Boulic Yiyu Cai Tolga Capin Marc Cavazza Bing-Yu Chen Yiorgos Chrysanthou Sabine Coquillart Frederic Cordier Justin Dauwels Etienne De-Sevin Zhi-Gang Deng Fabian Di Fiore Yves Duthen Arjan Egges Abdennour El Rhalibi Petros Faloutsos Ugur Gudukbay Mario Gutierrez James Hahn Ying He Shi-Min Hu Zhiyong Huang Veysi Isler Jean-Pierre Jessel Sophie Joerg Chris Joslin Prem Kalra Mustafa Kasap Scott King Taku Komura Caroline Larboulette Rynson Lau Wonsook Lee Tsai-Yen Li Ming Lin Anderson Maciel Nadia Magnenat Thalmann Dinesh Manocha Rachel Mcdonnell Franck Multon Soraia Musse Junyong Noh Igor Pandzic George Papagiannakis Laura Papaleo Nuria Pelechano Christopher Peters Julien Pettre Flavien Picon Tiberiu Popa Nicolas Pronost Isaac Rudomin Hyewon Seo Hubert Shum Matthias Teschner Daniel Thalmann Xin Tong Andy W. H. Khong Huamin Wang Jun Wang Enhua Wu Junsong Yuan Cem Yuksel Zerrin Yumak Jian Zhang Zhengyou Zhang Jianmin Zheng

This paper introduces a technique to analyze and visualize social networks using Shannon's entropy model. Entropy is exploited to measure the information amount in social network graphs, and to conduct sensitivity analyses. Novel measures such as degree, betweenness and closeness entropies are evaluated to find the change in graph entropy or the actors. In this work we present a visualization approach that uses coloring, sizing and filtering to help the users perceive the communicated information. The result of sensitivity analyses is integrated into the visualization using the change amount caused by the actors as information. The main contribution of this study is a visualization where the information communicated from a social network is enhanced by the help of sensitivity analyses.

Many professional tasks such as geographic or archaeological surveying require editing and processing spatial data. User generated models act as an underlying level for visualizing annotations. For accurate and fast placement of annotations in the field we introduce a mobile modelling workflow. Our contribution includes i) a novel annotation technique based on geometric regions and ii) a modelling workflow optimized for mobile devices.

Real-time rendering of large animated crowds consisting thousands of virtual humans is important for several applications including simulations, games and interactive walkthroughs, but cannot be performed using complex polygonal models at interactive frame rates. For that reason, several methods using large numbers of pre-computed image-based representations, which are called as impostors, have been proposed. These methods take the advantage of existing programmable graphics hardware to compensate the computational expense while maintaining the visual fidelity. Making the number of different virtual humans, which can be rendered in real-time, not restricted anymore by the required computational power but by the texture memory consumed for the variety and discretization of their animations. In this work, we proposed an alternative method that reduces the memory consumption by generating compelling intermediate textures using image-morphing techniques. In order to demonstrate the preserved perceptual quality of animations, where half of the key-frames were rendered using the proposed methodology, we have implemented the system using the graphical processing unit and obtained promising results at interactive frame rates.

Crowds must be simulated believable in terms of their appearance and behavior to improve a virtual environment's realism. Due to the complex nature of human behavior, realistic behavior of agents in crowd simulations is still a challenging problem. In this paper, we propose a novel behavioral model which builds analytical maps to control agents’ behavior adaptively with agent–crowd interaction formulations. We introduce information theoretical concepts to construct analytical maps automatically. Our model can be integrated into crowd simulators and enhance their behavioral complexity. We made comparative analyses of the presented behavior model with measured crowd data and two agent-based crowd simulators.

The availability of intuitive, user-friendly and specialized software to work with 3D models of cultural heritage artifacts is as important as the availability of low-cost and robust data acquisition techniques for the adoption of digitized 3D models in cultural heritage research. As recent developments in 3D scanning technologies have made the digitization of artifacts affordable; the amount of digitized models available for research increases rapidly. Consequently the need for specialized software for cultural heritage research and practice on 3D models becomes more apparent. The lack of spatial measurement tools familiar to cultural heritage experts in traditional 3D modeling packages motivated us to create a simple, freely available, and extensible measurement tools system, CH Toolbox, which was designed exclusively for cultural heritage research. The proposed system visualizes digitized models of artifacts in 3D and allows the user to analyze the pieces using a spaceball and mouse driven bi-manual interface. We describe here the components of the CH Toolbox system, specifically the virtual tape measure, caliper, rim chart and a surface area estimation tool. Additionally, we present justification for CH Toolbox's bi-manual interaction scheme according to Guiard's Kinematic Chain model for asymmetric human skilled bi-manual actions.

Maestro - 3D group calendar visualizer aims at handling multiple schedules and highlighting common free times. One of the most powerful skills of Maestro is scalability according to the number of group members, which can be up to 18 users. The use of color and shape intends to create a more lucid picture of an organization’s schedule, as opposed to traditional calendars which can overwhelm the user with information. The goal is not to produce yet another calendar application, but to define an interactive information visualization technique. This work concentrates on highlighting the relevant information, using primitive shapes and color differentiation to avoid a complicated depiction.

This paper reports on a transdisciplinary undergraduate university course designed to bring together fine art/visual communication design and computer science students for the creation and implementation of collaborative visual/audial projects that draw upon the specialised knowledge of both these disciplines. While an overview of syllabus and teaching methodologies is undertaken in the introduction, the focus of the paper concentrates upon an in-depth discussion and analysis of 3 specific projects that were developed by 3 distinct teams of students comprised of one artist/designer and one engineer.

Current virtual reality technologies provide many ways to interact with virtual humans. Most of those techniques, however, are limited to synthetic elements and require cumbersome sensors. We have combined a real-time simulation and rendering platform with a real-time, non-invasive vision-based recognition system to investigate interactions in a mixed environment with real and synthetic elements. In this paper, we present the resulting system, the example of a checkers game between a real person and an autonomous virtual human to demonstrate its performance.

In this paper we present a new framework in Augmented Reality context for rapid evaluation of prototypes before manufacture. The design of such prototypes is a time consuming process, leading t o the need of previous evaluation in realistic interactive environments. We have extended the definition of modelling object geometry with modelling object behaviour being able to evaluate them in a mixed environment. Such enhancements allow the development of tools and methods to test object behaviour, and perform interactions between real virtual humans and complex real and virtual objects.We propose a framework for testing the design of objects i an augmented reality context, where a virtual human is able to perform evaluation tests with an object composed of rea and virtual components. In this paper our framework is described and a case study is presented.

The authors present a novel approach to participant embodiment in networked collaborative virtual environments. The embodiment approach integrates live video into 3D objects for a hybrid participant representation. They implemented their ideas in a Networked Collaborative Virtual Environment system, VLNET and investigated network and rendering issues in comparison with virtual human participant embodiment. The paper presents two distinct case studies demonstrating their ideas. The first one is a tele-teaching application, in which they investigate a shared environment with virtual humans and hybrid embodiments. The second one presents a distributed augmented reality application, in which participants share a mixed environment with real and virtual elements.

Interaction between real and virtual humans covers a wide range of topics from creation and animation of virtual actors to computer vision techniques for data acquisition from real world. We discuss the design and implementation of an augmented reality system which allows investigation of different real/virtual interaction aspects. As an example we present an application to create real time interactive drama with real and virtual actors.