An Evolutionary Signature for Animated Meshes

Guoliang Luo, Haopeng Lei, Yugen Yi, Yuhua Li, Chuahua Xian
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Abstract

With the rapid growing advancement of animation technologies, 3D animated meshes are becoming one of the major data in the industry such as virtual reality. However, treating the animated mesh data efficiently remains a challenging task due to its large scale and limited feature descriptors. In this paper, we present an evolutionary signature for animated meshes based on tempo-spatial segmentation. In specific, we first conduct temporal segmentation to a given animated meshes with sub-motions, then apply spatial segmentation within each temporal segment, and intersect spatial segmentation result for over segmentation. Thirdly, we represent the segmentation results into graphs. Finally, we devise an edge evolution matrix based on the dynamic behaviour of each edge for the evolutionary signature of the input animated mesh. Our experimental results on similarity measurement by using the proposed signature reflect the effectiveness of our method.
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随着动画技术的飞速发展,三维动画网格正在成为虚拟现实等行业的主要数据之一。然而,由于动画网格数据的大规模和有限的特征描述符,有效地处理这些数据仍然是一项具有挑战性的任务。本文提出了一种基于时空分割的动态网格演化特征。具体而言,我们首先对给定的具有子运动的动画网格进行时间分割,然后在每个时间段内应用空间分割,并交叉空间分割结果进行过分割。第三,我们将分割结果表示成图形。最后,我们设计了一个基于每条边的动态行为的边缘演化矩阵,用于输入动画网格的演化特征。本文的相似度度量实验结果反映了本文方法的有效性。
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