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首页> 外文期刊>The Visual Computer >Fast hierarchical animated object decomposition using approximately invariant signature
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Fast hierarchical animated object decomposition using approximately invariant signature

机译:使用近似不变的签名快速分层动画对象分解

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摘要

In this paper, we introduce a novel method to hierarchically decompose the animated 3d object efficiently by utilizing high-dimensional and multi-scale geometric information. The key idea is to treat the animated surface sequences as a whole and extract the near-rigid components from it. Our approach firstly detects a set of the multi-scale feature points on the animated object and computes approximately invariant signature vectors for these points. Then, exploiting both the geometric attributes and the local signature vector of each point (vertex) of the animated object, all the points (vertices) of the animated object can be clustered efficiently using a GPU-accelerated mean shift clustering algorithm. To refine the decomposition boundaries, the initially-generated boundaries of the animated object can be further improved by applying a boundary refinement technique based on Gaussian Mixture Models (GMMs). Furthermore, we propose a hierarchical decomposition technique using a topology merging strategy without introducing additional computations. Our animated object decomposition approach does not require the topological connectivity of the animated object, thus it can be applied for both triangle mesh and point-sampled geometry sequences. The experimental results demonstrate that our method achieves both good quality results and high performance for the decomposition of animated object.
机译:在本文中,我们介绍了一种新颖的方法,可以利用高维和多尺度几何信息有效地对动画3d对象进行分层分解。关键思想是将动画曲面序列作为一个整体进行处理,并从中提取近乎刚性的分量。我们的方法首先检测动画对象上的一组多尺度特征点,并为这些点计算近似不变的特征向量。然后,利用动画对象的每个点(顶点)的几何属性和局部特征向量,可以使用GPU加速的均值漂移聚类算法有效地对动画对象的所有点(顶点)进行聚类。为了细化分解边界,可以通过应用基于高斯混合模型(GMM)的边界细化技术来进一步改善动画对象的初始生成的边界。此外,我们提出了一种使用拓扑合并策略的层次分解技术,而无需引入其他计算。我们的动画对象分解方法不需要动画对象的拓扑连接,因此可以应用于三角形网格和点采样几何序列。实验结果表明,我们的方法在动画对象分解方面取得了很好的质量效果和高性能。

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