面向非结构化网格序列分割的局部测地线直方图形状描述符

T. Mukasa, S. Nobuhara, Tony Tung, T. Matsuyama
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引用次数: 0

摘要

提出了一种新的基于拓扑的三维视频序列分割的形状描述符。3D视频是一系列没有时间对应的3D网格,有利于压缩、运动分析和运动编辑等应用。在3D视频中,3D网格连通性和全局表面拓扑结构都可以逐帧改变。这个特性阻止了通过整个3D网格系列进行精确的时间对应。为了克服这一困难,我们提出了一种两步策略,即使用我们的新形状描述符将整个序列分解为一系列拓扑一致的片段,然后在每个片段的基础上估计时间对应。通过获取时间对应关系,我们可以从预处理后的三维视频片段中提取刚体部分,建立部分运动结构,并将其整合成一个统一的运动模型来描述三维视频序列中的整个运动。在具有较大非刚体运动和重构误差的实际数据上证明了该形状描述符的鲁棒性和准确性。
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Part-wise Geodesic Histogram Shape Descriptor for Unstructured Mesh Series Segmentation
This paper presents a novel shape descriptor for topology-based segmentation of 3D video sequences. 3D video is a series of 3D meshes without temporal correspondences which benefit for applications including compression, motion analysis, and kinematic editing. In 3D video, both 3D mesh connectivities and the global surface topology can change frame by frame. This characteristic prevents from making accurate temporal correspondences through the entire 3D mesh series. To overcome this difficulty, we propose a two-step strategy which decomposes the entire sequence into a series of topologically coherent segments using our new shape descriptor, and then estimates temporal correspondences on a per-segment basis. As the result of acquiring temporal correspondences, we could extract rigid parts from the preprocessed 3D video segments to establish partial kinematic structures, and could integrate them into a single unified kinematic model which describes the entire kinematic motion in the 3D video sequence. We demonstrate the robustness and accuracy of the shape descriptor on real data which consist of large non-rigid motion and reconstruction errors.
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IPSJ Transactions on Computer Vision and Applications
IPSJ Transactions on Computer Vision and Applications Computer Science-Computer Vision and Pattern Recognition
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