Browsing by Author "Deng, Zhigang"

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    A Color-Pair Based Approach for Accurate Color Harmony Estimation
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Yang, Bailin; Wei, Tianxiang; Fang, Xianyong; Deng, Zhigang; Li, Frederick W. B.; Ling, Yun; Wang, Xun; Lee, Jehee and Theobalt, Christian and Wetzstein, Gordon
    Harmonious color combinations can stimulate positive user emotional responses. However, a widely open research question is: how can we establish a robust and accurate color harmony measure for the public and professional designers to identify the harmony level of a color theme or color set. Building upon the key discovery that color pairs play an important role in harmony estimation, in this paper we present a novel color-pair based estimation model to accurately measure the color harmony. It first takes a two-layer maximum likelihood estimation (MLE) based method to compute an initial prediction of color harmony by statistically modeling the pair-wise color preferences from existing datasets. Then, the initial scores are refined through a back-propagation neural network (BPNN) with a variety of color features extracted in different color spaces, so that an accurate harmony estimation can be obtained at the end. Our extensive experiments, including performance comparisons of harmony estimation applications, show the advantages of our method in comparison with the state of the art methods.
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    Curve Skeleton Extraction From 3D Point Clouds Through Hybrid Feature Point Shifting and Clustering
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Hu, Hailong; Li, Zhong; Jin, Xiaogang; Deng, Zhigang; Chen, Minhong; Shen, Yi; Benes, Bedrich and Hauser, Helwig
    Curve skeleton is an important shape descriptor with many potential applications in computer graphics, visualization and machine intelligence. We present a curve skeleton expression based on the set of the cross‐section centroids from a point cloud model and propose a corresponding extraction approach. We first provide the substitution of a distance field for a 3D point cloud model, and then combine it with curvatures to capture hybrid feature points. By introducing relevant facets and points, we shift these hybrid feature points along the skeleton‐guided normal directions to approach local centroids, simplify them through a tensor‐based spectral clustering and finally connect them to form a primary connected curve skeleton. Furthermore, we refine the primary skeleton through pruning, trimming and smoothing. We compared our results with several state‐of‐the‐art algorithms including the rotational symmetry axis (ROSA) and ‐medial methods for incomplete point cloud data to evaluate the effectiveness and accuracy of our method.
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    Hyperspectral Inverse Skinning
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Liu, Songrun; Tan, Jianchao; Deng, Zhigang; Gingold, Yotam; Benes, Bedrich and Hauser, Helwig
    In example‐based inverse linear blend skinning (LBS), a collection of poses (e.g. animation frames) are given, and the goal is finding skinning weights and transformation matrices that closely reproduce the input. These poses may come from physical simulation, direct mesh editing, motion capture or another deformation rig. We provide a re‐formulation of inverse skinning as a problem in high‐dimensional Euclidean space. The transformation matrices applied to a vertex across all poses can be thought of as a point in high dimensions. We cast the inverse LBS problem as one of finding a tight‐fitting simplex around these points (a well‐studied problem in hyperspectral imaging). Although we do not observe transformation matrices directly, the 3D position of a vertex across all of its poses defines an affine subspace, or flat. We solve a ‘closest flat’ optimization problem to find points on these flats, and then compute a minimum‐volume enclosing simplex whose vertices are the transformation matrices and whose barycentric coordinates are the skinning weights. We are able to create LBS rigs with state‐of‐the‐art reconstruction error and state‐of‐the‐art compression ratios for mesh animation sequences. Our solution does not consider weight sparsity or the rigidity of recovered transformations. We include observations and insights into the closest flat problem. Its ideal solution and optimal LBS reconstruction error remain an open problem.
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    Pacific Graphics 2023 - CGF 42-7: Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2023) Chaine, Raphaëlle; Deng, Zhigang; Kim, Min H.; Chaine, Raphaëlle; Deng, Zhigang; Kim, Min H.