In this paper, we present a novel approach for reconstructing garment sewing patterns from 2D garment images. Our method addresses the challenge of handling occlusion in 2D images by leveraging the symmetric and correlated nature of garment panels. We introduce a transformer-based deep neural network called Panelformer that learns the parametric space of garment sewing patterns. The network comprises two components: the panel transformer and the stitch predictor. The panel transformer estimates the parametric panel shapes, including the occluded panels, by learning from the visible ones. The stitch predictor determines the stitching information among the predicted panels, enabling the reconstruction of the complete garment. To mitigate the overfitting problem caused by strong panel correlations, we propose two tailor-made data augmentation techniques: panel masking and garment mixing. These techniques generate a wider variety of panel combinations, enhancing the model’s robustness and generalization capability. We evaluate the effectiveness of Panelformer using a synthetic dataset with diverse garment types. The experimental results demonstrate that our method outperforms competing baselines and achieves comparable performance to NeuralTailor, which operates on 3D point cloud data. This validates the efficacy of our approach in the context of garment sewing pattern reconstruction. By utilizing 2D images as input, our method expands the potential applications of garment modeling and offers easy accessibility to end users. Our code is available online1.

Abstract Logos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden‐ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error‐prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc.

The vector graphics with gradient mesh can be attributed to their compactness and scalability; however, they tend to fall short when it comes to real-time editing due to a lack of real-time rasterization and an efficient editing tool for image details. In this paper, we encode global manipulation geometries and local image details within a hybrid vector structure, using parametric patches and detailed features for localized and parallelized thin-plate spline interpolation in order to achieve good compressibility, interactive expressibility, and editability. The proposed system then automatically extracts an optimal set of detailed color features while considering the compression ratio of the image as well as reconstruction error and its characteristics applicable to the preservation of structural and irregular saliency of the image. The proposed real-time vector representation makes it possible to construct an interactive editing system for detail-maintained image magnification and color editing as well as material replacement in cross mapping, without maintaining spatial and temporal consistency while editing in a raster space. Experiments demonstrate that our representation method is superior to several state-of-the-art methods and as good as JPEG, while providing real-time editability and preserving structural and irregular saliency information.

This paper presents a novel algorithm to generate micrography QR codes, a novel machine-readable graphic generated by embedding a QR code within a micrography image. The unique structure of micrography makes it incompatible with existing methods used to combine QR codes with natural or halftone images. We exploited the high-frequency nature of micrography in the design of a novel deformation model that enables the skillful warping of individual letters and adjustment of font weights to enable the embedding of a QR code within a micrography. The entire process is supervised by a set of visual quality metrics tailored specifically for micrography, in conjunction with a novel QR code quality measure aimed at striking a balance between visual fidelity and decoding robustness. The proposed QR code quality measure is based on probabilistic models learned from decoding experiments using popular decoders with synthetic QR codes to capture the various forms of distortion that result from image embedding. Experiment results demonstrate the efficacy of the proposed method in generating micrography QR codes of high quality from a wide variety of inputs. The ability to embed QR codes with multiple scales makes it possible to produce a wide range of diverse designs. Experiments and user studies were conducted to evaluate the proposed method from a qualitative as well as quantitative perspective.

Human factor causes most of the road accidents; for improving traffic safety, advanced driver assistance system and autonomous driving have become active research. The most significant challenge of these systems is the development of a reliable obstacle detection which can recognize pedestrians and pedestrian-like objects on the road from color images and thermal images. Consequently, the object detection based on neural networks, such as YOLO [1] , is emerging as a solution for identifying obstacles with various appearance. Although the convolutional neural network provides a robust and reliable result, it still involves substantial computational costs and hard to port to an embedded device. This work intends to improve the performance of YOLO and aims at presenting a real-time obstacle detection system on an integrated device.

While the content of virtual reality (VR) has grown explosively in recent years, the advance of designing user-friendly control interfaces in VR still remains a slow pace. The most commonly used device, such as gamepad or controller, has fixed shape and weight, and thus can not provide realistic haptic feedback when interacting with virtual objects in VR. In this work, we present a novel and lightweight tracking system in the context of manipulating handheld objects in VR. Specifically, our system can effortlessly synchronize the 3D pose of arbitrary handheld objects between the real world and VR in realtime performance. The tracking algorithm is simple, which delicately leverages the power of Leap Motion and IMU sensor to respectively track object's location and orientation. We demonstrate the effectiveness of our system with three VR applications use pencil, ping-pong paddle, and smartphone as control interfaces to provide users more immersive VR experience.

Interacting with digital contents in 3D is an essential task in various applications such as modeling packages, gaming, virtual reality, etc. Traditional interfaces using keyboard and mouse or trackball usually require a non-trivial amount of working space as well as a learning process. We present the design of EZ-Manipulator, a new 3D manipulation interface using smartphones that supports mobile, fast, and ambiguity-free interaction with 3D objects. Our system leverages the built-in multi-touch input and gyroscope sensor of smartphones to achieve 9 degrees-of-freedom axis-constrained manipulation and free-form rotation. Using EZ-Manipulator to manipulate objects in 3D is easy. The user merely has to perform intuitive singleor two-finger gestures and rotate the hand-held device to perform manipulations at fine-grained and coarse levels respectively.We further investigate the ambiguity in manipulation introduced by indirect manipulations using a multi-touch interface, and propose a dynamic virtual camera adjustment to effectively resolve the ambiguity. A preliminary study shows that our system has significant lower task completion time compared to conventional use of a keyboard–mouse interface, and provides a positive user experience to both novices and experts.

With advances in the movie industry, composite interactions and complex visual effects require us to shoot at the designed part of a scene for immersion. Traditionally, the director of photography plans a camera path by recursively reviewing and commenting path-planning rendered results. Since the adjust-render-review process is not immediate and interactive, miscommunications happen to make the process ineffective and time consuming. Therefore, this paper proposes a What-You-See-What-You-Get camera path reviewing system for the director to interactively instruct and design camera paths. Our system consists of a camera handle, a parameter control board, and a camera tracking box with mutually perpendicular marker planes. When manipulating the handle, the attached camera captures markers on visible planes with selected parameters to adjust the world rendering view. The director can directly examine results to give immediate comments and feedbacks on transformation and parameter adjustment in order to achieve effective communication and reduce the reviewing time. Finally, we conduct a set of qualitative and quantitative evaluations to show that our system is robust and efficient and can provide means to give interactive and immediate instructions for effective communication and efficiency enhancement during path design.

High-resolution textures are determinant of not only high rendering quality in gaming and movie industries, but also of burdens in memory usage, data transmission bandwidth, and rendering efficiency. Therefore, it is desirable to shade 3D objects with vector images such as scalable vector graphics (SVG) for compactness and resolution independence. However, complicated geometry and high rendering cost limit the rendering effectiveness and efficiency of vector texturing techniques. In order to overcome these limitations, this paper proposes a real-time resolution-independent vector-embedded shading method for 3D animated objects. Our system first decomposes a vector image consisting of layered close coloring regions into unifying-coloring units for mesh retriangulation and 1D coloring texture construction, where coloring denotes color determination for a point based on an intermediate medium such as a raster/vector image, unifying denotes the usage of the same set of operations, and unifying coloring denotes coloring with the same-color computation operations. We then embed the coloring information and distances to enclosed unit boundaries in retriangulated vertices to minimize embedded information, localize vertex-embedded shading data, remove overdrawing inefficiency, and ensure fixed-length shading instructions for data compactness and avoidance of indirect memory accessing and complex programming structures when using other shading and texturing schemes. Furthermore, stroking is the process of laying down a fixed-width pen-centered element along connected curves, and our system also decomposes these curves into segments using their curve-mesh intersections and embeds their control vertices as well as their widths in the intersected triangles to avoid expensive distance computation. Overall, our algorithm enables high-quality real-time Graphics Processing Unit (GPU)-based coloring for real-time 3D animation rendering through our efficient SVG-embedded rendering pipeline while using a small amount of texture memory and transmission bandwidth.

Introducing motion into existing static paintings is becoming a field that is gaining momentum. This effort facilitates keeping artworks current and translating them to different forms for diverse audiences. Chinese ink paintings and Japanese Sumies are well recognized in Western cultures, yet not easily practiced due to the years of training required. We are motivated to develop an interactive system for artists, non-artists, Asians, and non-Asians to enjoy the unique style of Chinese paintings. In this paper, our focus is on replacing static water flow scenes with animations. We include flow patterns, surface ripples, and water wakes which are challenging not only artistically but also algorithmically. We develop a data-driven system that procedurally computes a flow field based on stroke properties extracted from the painting, and animate water flows artistically and stylishly. Technically, our system first extracts water-flow-portraying strokes using their locations, oscillation frequencies, brush patterns, and ink densities. We construct an initial flow pattern by analyzing stroke structures, ink dispersion densities, and placement densities. We cluster extracted strokes as stroke pattern groups to further convey the spirit of the original painting. Then, the system automatically computes a flow field according to the initial flow patterns, water boundaries, and flow obstacles. Finally, our system dynamically generates and animates extracted stroke pattern groups with the constructed field for controllable smoothness and temporal coherence. The users can interactively place the extracted stroke patterns through our adapted Poisson-based composition onto other paintings for water flow animation. In conclusion, our system can visually transform a static Chinese painting to an interactive walk-through with seamless and vivid stroke-based flow animations in its original dynamic spirits without flickering artifacts.

Manga are a popular artistic form around the world, and artists use simple line drawing and screentone to create all kinds of interesting productions. Vectorization is helpful to digitally reproduce these elements for proper content and intention delivery on electronic devices. Therefore, this study aims at transforming scanned Manga to a vector representation for interactive manipulation and real-time rendering with arbitrary resolution. Our system first decomposes the patch into rough Manga elements including possible borders and shading regions using adaptive binarization and screentone detector. We classify detected screentone into simple and complex patterns: our system extracts simple screentone properties for refining screentone borders, estimating lighting, compensating missing strokes inside screentone regions, and later resolution independently rendering with our procedural shaders. Our system treats the others as complex screentone areas and vectorizes them with our proposed line tracer which aims at locating boundaries of all shading regions and polishing all shading borders with the curve-based Gaussian refiner. A user can lay down simple scribbles to cluster Manga elements intuitively for the formation of semantic components, and our system vectorizes these components into shading meshes along with embedded Bézier curves as a unified foundation for consistent manipulation including pattern manipulation, deformation, and lighting addition. Our system can real-time and resolution independently render the shading regions with our procedural shaders and drawing borders with the curve-based shader. For Manga manipulation, the proposed vector representation can be not only magnified without artifacts but also deformed easily to generate interesting results.

Illusory motions refer to the phenomena in which static images composed of certain colors and patterns lead to the illusion of motions. This paper presents a first approach to generating illusory motions on 3D surfaces which can be used for shape illustration as well as artistic visualization of line fields on surfaces. Our method extends previous work on generating illusory motions in the plane, which we adapt to 3D surfaces. In addition, we propose novel Repeated Asymmetric Patterns (RAPs) to visualize bidirectional flows, thus enabling the visualization of line fields in the plane and on surfaces. We demonstrate the effectiveness of our method with applications in shape illustration as well as line field visualization on surfaces.

Field design has wide applications in graphics and visualization. One of the main challenges in field design has been how to provide users with both intuitive control over the directions in the field on one hand and robust management of its topology on the other hand. In this paper, we present a design paradigm for line fields that addresses this challenge. Rather than asking users to input all singularities as in most methods that offer topology control, we let the user provide a partitioning of the domain and specify simple flow patterns within the partitions. Represented by a selected set of harmonic functions, the elementary fields within the partitions are then combined to form continuous fields with rich appearances and well-determined topology. Our method allows a user to conveniently design the flow patterns while having precise and robust control over the topological structure. Based on the method, we developed an interactive tool for designing line fields from images, and demonstrated the utility of the fields in image stylization.

Abstract Mesh quadrangulation has received increasing attention in the past decade. While previous works have mostly focused on producing a high quality quad mesh of a single model, the connectivity of the quadrangulation is typically difficult to control and varies among models even with similar shapes. In this paper, we propose a novel interactive framework for quadrangulating a set of models collectively with compatible connectivity. Furthermore, we demonstrate its application to 3D mesh morphing. In our approach, the user interactively sketches a skeleton within each model, and our method automatically computes compatible base domains for all models from these skeletons, on which the models are parameterized. With this novel parameterization, it is very easy to generate a pleasing and smooth 3D morphing sequence among these compatible models. The method yields quadrangulation with comparable quality to existing approaches, but greatly simplifies compatible re‐meshing among a group of topologically equivalent models, in particular characters and animals models, with direct applications in shape blending and morphing. Copyright © 2009 John Wiley & Sons, Ltd.

We present a novel post-processing utility called adaptive geometry image (AGIM) for global parameterization techniques that can embed a 3D surface onto a rectangular1 domain. This utility first converts a single rectangular parameterization into many different tessellations of square geometry images(GIMs) and then efficiently packs these GIMs into an image called AGIM. Therefore, undersampled regions of the input parameterization can be up-sampled accordingly until the local reconstruction error bound is met. The connectivity of AGIM can be quickly computed and dynamically changed at rendering time. AGIM does not have T-vertices, and therefore no crack is generated between two neighboring GIMs at different tessellations. Experimental results show that AGIM can achieve significant PSNR gain over the input parameterization, AGIM retains the advantages of the original GIM and reduces the reconstruction error present in the original GIM technique. The AGIM is also for global parameterization techniques based on quadrilateral complexes. Using the approximate sampling rates, the PolyCube-based quadrilateral complexes with AGIM can outperform state-of-the-art multichart GIM technique in terms of PSNR.

Abstract Surface parameterization is a fundamental tool in computer graphics and benefits many applications such as texture mapping, morphing, and re‐meshing. Many spherical parameterization schemes with very nice properties have been proposed and widely used in the past. However, it is well known that the spherical parameterization is limited to genus‐0models. In this paper, we first propose a novel framework to extend spherical parameterization for handling a genus‐n surface. In this framework, we represent a surface S of arbitrary genus by a positive mesh O and several negative meshes Ni. Each negative surface is used to represent a hole. A positive surface O is obtained by removing all holes in the original surface S. Then, both positive and negative meshes are genus‐0 and can be spherically parameterized, respectively. To compute S, we can use a Boolean difference operation to subtract negative Nifrom a positive O. Next, we apply this novel framework to generate genus‐n‐to‐m mesh morphing application without restriction of n = m. Finally, there are many interesting non‐genus‐0 mesh morphing sequences generated. Copyright © 2006 John Wiley & Sons, Ltd.

Abstract This paper describes a new integrated scheme for metamorphosis between two closed manifold genus‐0 polyhedral models. Spherical parameterizations of the source and target models are created first. To control the morphing, any number of feature vertex pairs is specified and a fold‐over free warping method is used to align two spherical embeddings. Our method does not create a merged meta‐mesh or execute re‐meshing to construct a common connectivity for morphs. Alternatively, a scheme for the progressive connectivity transformation of two spherical parameterizations is employed to generate the intermediate meshes. A novel semi‐overlay with a geomorph scheme is proposed to reduce the popping effects caused by the connectivity transformation. We demonstrate several examples of aesthetically pleasing morphing sequences using the proposed scheme. Copyright © 2005 John Wiley & Sons, Ltd.