Abstract The capability to generate simulation‐ready garment models from 3D shapes of clothed people will significantly enhance the interpretability of captured geometry of real garments, as well as their faithful reproduction in the digital world. This will have notable impact on fields like shape capture in social VR, and virtual try‐on in the fashion industry. To align with the garment modeling process standardized by the fashion industry and cloth simulation software, it is required to recover 2D patterns, which are then placed around the wearer's body model and seamed prior to the draping simulation. This involves an inverse garment design problem, which is the focus of our work here: Starting with an arbitrary target garment geometry, our system estimates its animatable replica along with its corresponding 2D pattern. Built upon a differentiable cloth simulator, it runs an optimization process that is directed towards minimizing the deviation of the simulated garment shape from the target geometry, while maintaining desirable properties such as left‐to‐right symmetry. Experimental results on various real‐world and synthetic data show that our method outperforms state‐of‐the‐art methods in producing both high‐quality garment models and accurate 2D patterns.

Abstract As the symbol of beauty, floral objects have been one of the most popular subjects of artistic drawing. However, designing 3D floral models is generally time‐ and resource‐consuming, because of their structural and geometrical complexity. In this paper, we address the problem of reconstructing floral objects from sketch input. The user draws a relatively clean sketch of a flower and a few additional guide markings from an arbitrary view to rapidly create quality geometric models of flowers. Our system offers a novel modeling scheme compared to several existing flower modelers accepting sketch as input, where the user is required to work with different views, providing step‐by‐step sketch input. Given the silhouette and the guide strokes, an assumed, common botanical structure is estimated, i.e. a cone for each ring of petals. The cones and the silhouette sketch that we segment into elementary curves are used to retrieve model elements from the pre‐constructed shape database. These elements are then placed together around the cone, where an additional, per‐element deformation is performed so as to maximize the silhouette similarity between the user sketch and the 3D flower model from the chosen view. Our system has shown to robustly create a variety of flowers in various configurations, including flower models with several petal layers and various blooming degrees, drawn from different views.

Abstract Understanding the attentional behavior of the human visual system when visualizing a rendered 3D shape is of great importance for many computer graphics applications. Eye tracking remains the only solution to explore this complex cognitive mechanism. Unfortunately, despite the large number of studies dedicated to images and videos, only a few eye tracking experiments have been conducted using 3D shapes. Thus, potential factors that may influence the human gaze in the specific setting of 3D rendering, are still to be understood. In this work, we conduct two eye‐tracking experiments involving 3D shapes, with both static and time‐varying camera positions. We propose a method for mapping eye fixations (i.e., where humans gaze) onto the 3D shapes with the aim to produce a benchmark of 3D meshes with fixation density maps, which is publicly available. First, the collected data is used to study the influence of shape, camera position, material and illumination on visual attention. We find that material and lighting have a significant influence on attention, as well as the camera path in the case of dynamic scenes. Then, we compare the performance of four representative state‐of‐the‐art mesh saliency models in predicting ground‐truth fixations using two different metrics. We show that, even combined with a center‐bias model, the performance of 3D saliency algorithms remains poor at predicting human fixations. To explain their weaknesses, we provide a qualitative analysis of the main factors that attract human attention. We finally provide a comparison of human‐eye fixations and Schelling points and show that their correlation is weak.

The use of cost-efficient and portative devices, such as the Ki-nect, has facilitated the reconstruction of indoor scenes, which has become a field of interest to many. While a large number of applications have been developed for the accurate reconstruction of a scene through efficient registration of multiple scans, the scanning of the scene by the user remains a time-consuming process. This is particularly the case when the scan must not contain any missing data. In this paper, we propose a method requiring only a few shots without any overlapping requirement, which makes the scanning process very simple and light. Given a set point clouds (shots) sparsely taken from an indoor scene, our method seeks for transformations that align the shots together, creating an alignment graph at the same time. It then searches within this graph for the set of transformations corresponding to a possible solution, providing a reconstruction of the scene. Since our method allows missing views and can find all plausible solutions, it can be used to create new scenes by assembling shots obtained from different real or virtual scenes.

This paper presents an image-based rendering (IBR) system based on RGB-D images. The input of our system consists of RGB-D images captured at sparse locations in the scene and can be expanded by adding new RGB-D images. The sparsity of RGB-D images increases the usability of our system as the user need not capture a RGB-D image stream in a single shot, which may require careful planning for a hand-held camera. Our system begins with a single RGB-D image and images are incrementally added one by one. For each newly added image, a batch process is performed to align it with previously added images. The process does not include a global alignment step, such as bundle adjustment, and can be completed quickly by computing only local alignments of RGB-D images. Aligned images are represented as a graph, where each node is an input image and an edge contains relative pose information between nodes. A novel view image is rendered by picking the nearest input as the reference image and then blending the neighboring images based on depth information in real time. Experimental results with indoor scenes using Microsoft Kinect demonstrate that our system can synthesize high quality novel view images from a sparse set of RGB-D images.

We describe a method for modeling helices from planar curves. Given a polygonal curve in the ( x , y ) plane, the method computes a helix such that its orthogonal projection onto the ( x , y ) plane fits the polygonal curve . The helix curve is first sampled and the transformation matrix that best aligns points of the sampled helix to those of the polygonal curve is calculated. This transformation matrix is then used to estimate the parameters of the helix whose projection fits the polygonal curve.

Abstract This paper presents a new technique which makes use of deformation and motion properties between animated meshes for finding their spatial correspondences. Given a pair of animated meshes exhibiting a semantically similar motion, we compute a sparse set of feature points on each mesh and compute spatial correspondences among them so that points with similar motion behavior are put in correspondence. At the core of our technique is our new, dynamic feature descriptor named AnimHOG, which encodes local deformation characteristics. AnimHOG is ob‐tained by computing the gradient of a scalar field inside the spatiotemporal neighborhood of a point of interest, where the scalar values are obtained from the deformation characteristic associated with each vertex and at each frame. The final matching has been formulated as a discreet optimization problem that finds the matching of each feature point on the source mesh so that the descriptor similarity between the corresponding feature pairs as well as compatibility and consistency as measured across the pairs of correspondences are maximized. Consequently, reliable correspondences can be found even among the meshes of very different shape, as long as their motions are similar. We demonstrate the performance of our technique by showing the good quality of matching results we obtained on a number of animated mesh pairs.

We present an efficient and robust algorithm for the landmark transfer on 3D meshes that are approximately isometric. Given one or more custom landmarks placed by the user on a source mesh, our method efficiently computes corresponding landmarks on a family of target meshes. The technique is useful when a user is interested in characterization and reuse of application-specific landmarks on meshes of similar shape (for example, meshes coming from the same class of objects). Consequently, across a set of multiple meshes consistency is assured among landmarks, regardless of landmark geometric distinctiveness. The main advantage of our method over existing approaches is its low computation time. Differently from existing non-rigid registration techniques, our method detects and uses a minimum number of geometric features that are necessary to accurately locate the user-defined landmarks and avoids performing unnecessary full registration. In addition, unlike previous techniques that assume strict consistency with respect to geodesic distances, we adopt histograms of geodesic distance to define feature point coordinates, in order to handle the deviation of isometric deformation. This allows us to accurately locate the landmarks with only a small number of feature points in proximity, from which we build what we call a minimal graph. We demonstrate and evaluate the quality of transfer by our algorithm on a number of Tosca data sets.

ABSTRACT We describe a compression method for three‐dimensional animation sequences that has notable advantages over existing techniques. We first aggregate the frame data by similarity and reorganize them into clusters, which results in the sequence split into several motion fragments of varying lengths. To minimize the number of clusters and obtain optimal clustering, we perform frame alignment, which eliminates the “global” rigid transformation from each frame data and use only “pose” when evaluating the similarity between frames. We then apply principal component analysis for each cluster, from which we get coordinates of corresponding frames in a reduced dimension. Because similar frames are considered, the number of coefficients required for each frame becomes smaller; thus, we obtain better dimension reduction for a given reconstruction error. Further, we perform intracluster compression based on linear coding. Because every motion fragment presents similar frames, conventional linear predictive coding can be replaced by key frame‐based linear coding to achieve minimal reconstruction error. Results show that our method can obtain a high compression ratio, with a limited reconstruction error. Copyright © 2013 John Wiley & Sons, Ltd.

This paper presents a system to create mirror-symmetric surfaces from free-form sketches. The system takes as input a hand-drawn sketch and generates a surface whose silhouette approximately matches the input sketch. The input sketch typically consists of a set of curves connected at their endpoints, forming T-junctions and cusps. Our system is able to identify the skewed-mirror and translational symmetry between the hand-drawn curves and uses this information to reconstruct the occluded parts of the surface and its 3D shape.

Abstract Incense, candle smoke and cigarette smoke often exhibit smoke flows with a surface‐like appearance. Although delving into well‐known computational fluid dynamics may provide a solution to create such an appearance, we propose a much efficient alternative that combines a low‐resolution fluid simulation with explicit geometry provided by NURBS surfaces. Among a wide spectrum of fluid simulation, our algorithm specifically tailors to reproduce the semi‐transparent surface look and motion of the smoke. The main idea is that we follow the traces called streaklines created by the advected particles from a simulation and reconstruct NURBS surfaces passing through them. Then, we render the surfaces by applying an opacity map to each surface, where the opacity map is created by utilizing the smoke density and the characteristics of the surface contour. Augmenting the results from low‐resolution simulations such a way requires a low computational cost and memory usage by design.

Abstract We introduce in this paper a new method for smooth foldover‐free warping of images. It allows users to specify the constraints in two different ways: positional constraints to constrain the position of points in the image and gradient constraints to constrain the orientation and scaling of some parts of the image. We then show how our method is used for texture mapping with hard constraints. We start with an unconstrained planar embedding of the target mesh calculated with conventional methods. In order to obtain a mapping that satisfies the user‐defined constraints, we use our warping method to align the features of the texture image with those of the unconstrained embedding. Compared to previous work, our method generates a smoother texture mapping and offers higher level of control for defining the constraints.

Tight-fit cloth pressure provides important clue on how well a cloth fits to a body and thus on how comfortable the wearer feels with the cloth. Traditionally-used pressure sensor devices are expensive, sensitive to the experimental environment, and difficult to reproduce. In this paper, a physically-based cloth simulator has been tested for its usability as to measuring the cloth pressure, in order to replace physical measurement of cloth pressure that requires careful operation of pressure sensors. We use existing cloth simulator based on a particle system and measure spring forces exerted on each particle along its normal direction, divided by the summed area of triangles adjacent to that particle. To quantitatively validate the pressure values from the simulator, we have conducted comparative analysis on a set of thin-shell cylindrical tubes --- clothing pressure values have been measured by theoretical estimation and physical experiments using pressure sensors, and compared with those measured by the simulation. While their absolute pressure values differ from each other they exhibit a consistent tendency. From these comparative studies we concluded that cloth simulator can actually be used to measure tight-fit cloth pressure, and further conducted the clothing pressure measure on 3D human body models using the simulator.

Abstract The advent of 3D scanning technology has allowed effective measurement and analysis of breast size and shape, attracting interests by plastic surgeons, brassier designers, etc. Much work remains, however, before 3D scanning systems can be successfully used in automated analysis and synthesis of the breast—filtering noise, filling holes, and, in case a statistical analysis is desired, finding correspondence among each scan data. Moreover, analysis of a sagged breast is difficult to obtain, due to occlusions. In this paper, we address the problems and specific issues of using 3D scan data for the analysis and synthesis of breast models. The goal of our work is to build a breast modeler which can help both surgeons and garment designers in analyzing breast volume and surface measurements. Given enough samples of scanned breasts, our modeler can generate highly realistic breast shape, with some expected and consistent variability. Copyright © 2007 John Wiley & Sons, Ltd.

Abstract A data‐driven approach for the real‐time processing of clothes, particularly suitable for simulating dresses worn by virtual characters, is proposed. It starts, prior to real‐time simulation, by analyzing cloth behavior in relation to the underlying skeleton movement from a presimulated sequence of the cloth obtained using any high‐quality off‐line simulators. The idea is to use this analysis to find an optimal combination of physics‐based simulation and geometric approximation of the simulator; potentially colliding regions are defined on the cloth such that they will hold true for the skeleton movement that closely matches that of presimulated sequence. At runtime, using these analyses, our simulation process provides both visually pleasing results and performance, as long as the motion of the character remains sufficiently close to the original sequence used for the precomputation. The key contributions of this paper are (1) efficient collision handling that prunes out potentially colliding objects by using the off‐line simulation sequence as examples; (2) data‐driven fix‐up process for the coarse mesh simulation that deduces the gross behavior of the cloth; and (3) geometric approximation of the fine mesh deformation, responsible for details in the shape of the cloth such as wrinkles.

Although graphical human modeling has been a long sought subject in computer graphics, when it comes to dealing with real-time applications, it raises a number of unique requirements for both CG artists and researchers. For example, for a real-time performance it is highly desirable to lighten the geometry and optimize the runtime animation of characters wherever possible. An important need in such systems is to assist the CG artists in seamlessly transforming their modeling work from CG packages to the real-time application, without limiting their expressivity. In this paper we describe techniques by which dressed human characters are modeled, loaded into VR scenes, and simulated in real-time. In doing so, we point out challenging issues and solutions that such tasks imply at each phase of modeling and simulation. In particular, we turn our attention to what we consider as key technical components: body and clothes. Case studies show that our modelers successfully meet the need of real-time requirements over a wide variety of scenarios.

A data-driven approach for real-time processing of clothes, particularly suitable for simulating dresses worn by virtual characters, is proposed. It starts, prior to realtime simulation, by analyzing cloth behavior in relation to the underlying skeleton movement from a pre-simulated sequence of the cloth obtained using any high quality offline simulators. The idea is to use this analysis to find an optimal combination of physics-based simulation and geometric approximation of the simulator; potentially colliding regions are defined on the cloth such that they will hold true for the skeleton movement that closely matches that of pre-simulated sequence. At runtime, using these analyses, our simulation process provides both visually pleasing results and performance, as long as the motion of the character remains sufficiently close to the original sequence used for the pre-computation. The key contributions of this paper are (1) efficient collision handling that prunes out potentially colliding objects by using the off-line simulation sequence as examples; (2) data-driven fix-up process for the coarse mesh simulation that deduces the gross behavior of the cloth; and (3) geometric approximation of the fine mesh deformation, responsible for details in the shape of the cloth such as wrinkles.

In most vehicle simulators, complete physical mockups equipped with steering wheel, gearshift and pedals are required. These devices are essential in trying to simulate real conditions, but as a drawback the system becomes expensive, huge (non mobile), and limited to reflect changes on the vehicle type, dimensions, or interior design. We have implemented different configurations for an immersive vehicle simulator, ranging from the use of a real mockup equipped with force-feedback steering wheel, gearshift and pedals, to fully virtual control metaphors, which are based only on trackers and datagloves. We propose such fully virtual control metaphors as an alternative to minimize the use of physical devices in simulators.

While mechanical cloth simulation systems are widely used for creating draped garments on virtual characters, the animation of virtual garments raise challenges on its own. The perception of garment beauty is first related to the dynamic accuracy of the cloth simulation model, which has to reproduce precisely the dissipative behaviors of the material, such as viscosity and plasticity, rendering the visual features of realistic cloth motion. The other important aspect is the need of adequate techniques for the real-time visualization of animated virtual garments, required for many real-time or interactive applications. This work present techniques yielding visible advances for addressing these two aspects.

In this paper, we describe a method for cloth animation in real-time. The algorithm works in a hybrid manner exploiting the merits of both the physical-based and geometric deformations. It makes use of predetermined conditions between the cloth and the body model, avoiding complex collision detection and physical deformations wherever possible. Garments are segmented into pieces that are simulated by various algorithms, depending on how they are laid on the body surface and whether they stick or flow on it. Tests show that the method is well suited to fully dressed virtual human models, achieving real-time performance compared to ordinary cloth-simulations.

Abstract In this paper, we present a framework for both skin and cloth deformation. Traditionally, skin and cloth deformations are managed by a non‐unified strategy although the skin interacts on clothes and vice versa. In general, the skin is considered as a rigid surface on which the clothes have no effect. We propose in this paper a unified approach for cloth and body deformation. Our system is able to handle both skin and cloth deformation with collision response. These deformations are managed with a particle system. The skin deformation model is a hybrid model, where deformation due to the skeleton motion is controlled geometrically, and where the collision response is handled by a physical‐based model. In case of collision among skin and clothes, a reaction and friction forces are applied on both skin and cloth to avoid penetration. Copyright © 2001 John Wiley & Sons, Ltd.

We present an integrated system for skin deformation that is able to handle deformations due to both the skeleton animation and collisions. This method is based on a physically-based deformation of a skin surface linked to a reference shape; the reference shape is animated with a geometric deformation. Collision detection has been implemented to avoid penetration. Our method for collision response consists of a kinematical correction of positions and forces during the simulation. The resulting model of the skin deformation enables an efficient simulation and interaction of the skin with deformable objects. Results are presented as examples.

We present a system for the animation of a human hand that plays violin. A neural network controls the hand movement. We make use of an optimization method to generate examples for the neural network training. The musical decision of which finger to use is automatically made by best first search. We show that the movements of the violinist's hands are physically and musically feasible, and that the musical decisions are consistent with those recommended in the violin pedagogy. A description of the system, the results of the decisions, and the animations are presented.

Medical imaging can provide data for useful views of the interior details of human anatomy. In addition to visualization, which in general has been the primary reason for obtaining these data, many other uses are possible. These include modeling of different elements and their inter-relationships-topological modeling, simulation of physical processes, analysis of movements, and validation of models. Here, we describe some of the modeling issues from medical imaging. The issues are particularly related to topological modeling of different anatomical elements: bones, muscles, articulations, etc. A three-dimensional topological modeler is presented with which anatomists and other users can build a topological database containing structural, topological, and mechanical information of anatomical elements.