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The need to plan motions for agents with variable shape constraints such as under different formations appears in several virtual and real-world applications of autonomous agents. In this work, we focus on planning and execution of formation-aware paths for a group of agents traversing a cluttered environment. The proposed planning framework addresses the trade-off between being able to enforce a preferable formation when traversing the corridors of the environment, versus accepting to switch to alternative formations requiring less clearance in order to utilize narrower corridors that can lead to a shorter overall path to the final destination. At the planning stage, this trade-off is addressed with a multi-layer graph annotated with per-layer navigation costs and formation transition costs, where each layer represents one formation together with its specific clearance requirement. At the navigation stage, we introduce Corridor Shortest Path Maps (CSPMs), which produce a vector field for guiding agents along the solution corridor, ensuring unobstructed in-formation navigation in cluttered environments, as well as group motion along lengthwise-optimal paths in the solution corridor. We also present examples of how our multi-layer planning framework can be applied to other types of multi-modal planning problems.This work addresses multi-formation path planning and navigation in cluttered environments. A new multi-layer graph construction and search methodology is proposed for computing global solutions considering formation preferences and required clearances. At the navigation level we introduce Corridor Shortest Path Maps for achieving unobstructed in-formation group navigation.image
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Computational models, such as simulations, are central to a wide range of fields in science and industry. Those models take input parameters and produce some output. To fully exploit their utility, relations between parameters and outputs must be understood. These include, for example, which parameter setting produces the best result (optimization) or which ranges of parameter settings produce a wide variety of results (sensitivity). Such tasks are often difficult to achieve for various reasons, for example, the size of the parameter space, and supported with visual analytics. In this paper, we survey visual parameter space exploration (VPSE) systems involving spatial and temporal data. We focus on interactive visualizations and user interfaces. Through thematic analysis of the surveyed papers, we identify common workflow steps and approaches to support them. We also identify topics for future work that will help enable VPSE on a greater variety of computational models.
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<div class="JournalArticle Publication short-list"> <div class="authors"> <span class="author-name" > Piccolotto, Nikolaus ✉ </span> <span class="author-type"> </span> ; <span class="author-name" > Boegl, Markus </span> <span class="author-type"> </span> ; <span class="author-name" > Miksch, Silvia </span> <span class="author-type"> </span> </div ><div class="title"><a href="/gui2/?mode=browse¶ms=publication;33924428" mtid="33924428" target="_blank">Visual Parameter Space Exploration in Time and Space</a></div> <div class="pub-info"> <span class="journal-title">COMPUTER GRAPHICS FORUM</span> <span class="journal-volume"></span> <span class="page"> , 32 p. </span> <span class="year">(2023)</span> </div> <div class="pub-end"><div class="identifier-list"> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:black" title="10.1111/cgf.14785" target="_blank" href="https://doi.org/10.1111/cgf.14785"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="000961689300001" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/000961689300001"> WoS </a> </span> </span> </div> <div class="short-pub-prop-list"> <span class="short-pub-mtid"> Közlemény:33924428 </span> <span class="status-holder"><span class="status-data status-VALIDATED"> Egyeztetett </span></span> <span class="pub-core"> Idéző </span> <span class="pub-type">Folyóiratcikk (Szakcikk ) </span> <!-- && !record.category.scientific --> <span class="pub-category">Tudományos</span> </div> </div> </div><div class="JournalArticle Publication long-list">
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3D object matching and registration on point clouds are widely used in computer vision. However, most existing point cloud registration methods have limitations in handling non-rigid point sets or topology changes (e.g. connections and separations). As a result, critical characteristics such as large inter-frame motions of the point clouds may not be accurately captured. This paper proposes a statistical algorithm for non-rigid point sets registration, addressing the challenge of handling topology changes without the need to estimate correspondence. The algorithm uses a novel Break and Splice framework to treat the non-rigid registration challenges as a reproduction process and a Dirichlet Process Gaussian Mixture Model (DPGMM) to cluster a pair of point sets. Labels are assigned to the source point set with an iterative classification procedure, and the source is registered to the target with the same labels using the Bayesian Coherent Point Drift (BCPD) method. The results demonstrate that the proposed approach achieves lower registration errors and efficiently registers point sets undergoing topology changes and large inter-frame motions. The proposed approach is evaluated on several data sets using various qualitative and quantitative metrics. The results demonstrate that the Break and Splice framework outperforms state-of-the-art methods, achieving an average error reduction of about 60% and a registration time reduction of about 57.8%.
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<div class="JournalArticle Publication short-list"> <div class="authors"> <span class="author-name" > Gao, Qinghong ✉ </span> <span class="author-type"> </span> ; <span class="author-name" > Zhao, Yan </span> <span class="author-type"> </span> ; <span class="author-name" > Xi, Long </span> <span class="author-type"> </span> ; <span class="author-name" > Tang, Wen </span> <span class="author-type"> </span> ; <span class="author-name" > Wan, Tao Ruan </span> <span class="author-type"> </span> </div ><div class="title"><a href="/gui2/?mode=browse¶ms=publication;33840548" mtid="33840548" target="_blank">Break and Splice: A Statistical Method for Non-Rigid Point Cloud Registration</a></div> <div class="pub-info"> <span class="journal-title">COMPUTER GRAPHICS FORUM</span> <span class="journal-volume"></span> <span class="page"> , 19 p. </span> <span class="year">(2023)</span> </div> <div class="pub-end"><div class="identifier-list"> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:black" title="10.1111/cgf.14788" target="_blank" href="https://doi.org/10.1111/cgf.14788"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="000947732500001" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/000947732500001"> WoS </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:black" title="85149819033" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85149819033"> Scopus </a> </span> </span> </div> <div class="short-pub-prop-list"> <span class="short-pub-mtid"> Közlemény:33840548 </span> <span class="status-holder"><span class="status-data status-VALIDATED"> Egyeztetett </span></span> <span class="pub-core"> Idéző </span> <span class="pub-type">Folyóiratcikk (Szakcikk ) </span> <!-- && !record.category.scientific --> <span class="pub-category">Tudományos</span> </div> </div> </div><div class="JournalArticle Publication long-list">
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<div class="title"><a href="/gui2/?mode=browse¶ms=publication;33840548" target="_blank">Break and Splice: A Statistical Method for Non-Rigid Point Cloud Registration</a></div> <div> <span class="journal-title">COMPUTER GRAPHICS FORUM</span>
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Efficiently optimizing the internal structure of 3D printing models is a critical focus in the field of industrial manufacturing, particularly when designing self-supporting structures that offer high stiffness and lightweight characteristics. To tackle this challenge, this research introduces a novel approach featuring a self-supporting polyhedral structure and an efficient optimization algorithm. Specifically, the internal space of the model is filled with a combination of self-supporting octahedrons and tetrahedrons, strategically arranged to maximize structural integrity. Our algorithm optimizes the wall thickness of the polyhedron elements to satisfy specific stiffness requirements, while ensuring efficient alignment of the filled structures in finite element calculations. Our approach results in a considerable decrease in optimization time. The optimization process is stable, converges rapidly, and consistently delivers effective results. Through a series of experiments, we have demonstrated the effectiveness and efficiency of our method in achieving the desired design objectives.
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In this paper, we tackle the challenging problem of 3D keypoint estimation of general objects using a novel implicit representation. Previous works have demonstrated promising results for keypoint prediction through direct coordinate regression or heatmap-based inference. However, these methods are commonly studied for specific subjects, such as human bodies and faces, which possess fixed keypoint structures. They also suffer in several practical scenarios where explicit or complete geometry is not given, including images and partial point clouds. Inspired by the recent success of advanced implicit representation in reconstruction tasks, we explore the idea of using an implicit field to represent keypoints. Specifically, our key idea is employing spheres to represent 3D keypoints, thereby enabling the learnability of the corresponding signed distance field. Explicit key-points can be extracted subsequently by our algorithm based on the Hough transform. Quantitative and qualitative evaluations also show the superiority of our representation in terms of prediction accuracy.
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<div class="JournalArticle Publication short-list"> <div class="authors"> <span class="author-name" > Zhu, Xiangyu </span> <span class="author-type"> </span> ; <span class="author-name" > Du, Dong </span> <span class="author-type"> </span> ; <span class="author-name" > Huang, Haibin </span> <span class="author-type"> </span> ; <span class="author-name" > Ma, Chongyang </span> <span class="author-type"> </span> ; <span class="author-name" > Han, Xiaoguang ✉ </span> <span class="author-type"> </span> </div ><div class="title"><a href="/gui2/?mode=browse¶ms=publication;34364172" mtid="34364172" target="_blank">3D Keypoint Estimation Using Implicit Representation Learning</a></div> <div class="pub-info"> <span class="journal-title">COMPUTER GRAPHICS FORUM</span> <span class="journal-volume">42</span> : <span class="journal-issue">5</span> <span class="page"> , 12 p. </span> <span class="year">(2023)</span> </div> <div class="pub-end"><div class="identifier-list"> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:black" title="10.1111/cgf.14917" target="_blank" href="https://doi.org/10.1111/cgf.14917"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="001046155600001" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/001046155600001"> WoS </a> </span> </span> </div> <div class="short-pub-prop-list"> <span class="short-pub-mtid"> Közlemény:34364172 </span> <span class="status-holder"><span class="status-data status-VALIDATED"> Egyeztetett </span></span> <span class="pub-core"> Idéző </span> <span class="pub-type">Folyóiratcikk (Szakcikk ) </span> <!-- && !record.category.scientific --> <span class="pub-category">Tudományos</span> </div> </div> </div><div class="JournalArticle Publication long-list">
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We present a novel graph-based simulation approach for generating micro wrinkle geometry on human skin, which can easily scale up to the micro-meter range and millions of wrinkles. The simulation first samples pores on the skin and treats them as nodes in a graph. These nodes are then connected and the resulting edges become candidate wrinkles. An iterative optimization inspired by pedestrian trail formation is then used to assign weights to those edges, i.e., to carve out the wrinkles. Finally, we convert the graph to a detailed skin displacement map using novel shape functions implemented in graphics shaders. Our simulation and displacement map creation steps expose fine controls over the appearance at real-time framerates suitable for interactive exploration and design. We demonstrate the effectiveness of the generated wrinkles by enhancing state-of-art 3D reconstructions of real human subjects with simulated micro wrinkles, and furthermore propose an artist-driven design flow for adding micro wrinkles to fictional characters.
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<div class="JournalArticle Publication short-list"> <div class="authors"> <span class="author-name" > Weiss, S. ✉ </span> <span class="author-type"> </span> ; <span class="author-name" > Moulin, J. </span> <span class="author-type"> </span> ; <span class="author-name" > Chandran, P. </span> <span class="author-type"> </span> ; <span class="author-name" > Zoss, G. </span> <span class="author-type"> </span> ; <span class="author-name" > Gotardo, P. </span> <span class="author-type"> </span> ; <span class="author-name" > Bradley, D. </span> <span class="author-type"> </span> </div ><div class="title"><a href="/gui2/?mode=browse¶ms=publication;34263772" mtid="34263772" target="_blank">Graph-Based Synthesis for Skin Micro Wrinkles</a></div> <div class="pub-info"> <span class="journal-title">COMPUTER GRAPHICS FORUM</span> <span class="journal-volume">42</span> : <span class="journal-issue">5</span> <span class="page"> Paper: e14904 , 12 p. </span> <span class="year">(2023)</span> </div> <div class="pub-end"><div class="identifier-list"> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="10.1111/cgf.14904" target="_blank" href="https://doi.org/10.1111/cgf.14904"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="001052660400008" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/001052660400008"> WoS </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="85176004337" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85176004337"> Scopus </a> </span> </span> </div> <div class="short-pub-prop-list"> <span class="short-pub-mtid"> Közlemény:34263772 </span> <span class="status-holder"><span class="status-data status-VALIDATED"> Egyeztetett </span></span> <span class="pub-core"> Idéző </span> <span class="pub-type">Folyóiratcikk (Szakcikk ) </span> <!-- && !record.category.scientific --> <span class="pub-category">Tudományos</span> </div> </div> </div><div class="JournalArticle Publication long-list">
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<div class="title"><a href="/gui2/?mode=browse¶ms=publication;34263772" target="_blank">Graph-Based Synthesis for Skin Micro Wrinkles</a></div> <div> <span class="journal-title">COMPUTER GRAPHICS FORUM</span>
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<pre class="comment" style="margin-top: 0; margin-bottom: 0;"><u>Megjegyzés</u>: DisneyResearch|Studios, United States
Industrial Light & Magic, United States
Export Date: 17 November 2023
CODEN: CGFOD</pre>
</div></div>