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Non-rigid object tracking with elastic structure of local patches and hierarchical sampling

机译:具有局部补丁弹性结构和分层采样的非刚性物体跟踪

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To solve the problem of real-time object tracking under partial occlusions and non-rigid deformations, we propose a tracking method based on sequential Bayesian inference. The proposed method is mainly consisted of two parts: (1) modeling the target object using elastic structure of local patches for robust performance; and (2) efficient hierarchical sampling method to obtain an acceptable solution in real-time. The elastic structure of local patches allows the proposed method to handle partial occlusions and non-rigid deformations through the relationship among neighboring patches. The proposed hierarchical sampling method generate samples from the region where the posterior is concentrated to reduce computation time. The method is extensively tested on a number of challenging image sequences with occlusion and non-rigid deformation, demonstrating its real-time capability and robustness under di#erent situations.
机译:为解决部分遮挡和非刚性变形下的实时目标跟踪问题,提出了一种基于顺序贝叶斯推理的目标跟踪方法。所提出的方法主要由两部分组成:(1)利用局部补丁的弹性结构对目标对象进行建模,以提高鲁棒性能。 (2)高效的分层抽样方法,实时获得可接受的解决方案。局部斑块的弹性结构允许所提出的方法通过相邻斑块之间的关系来处理部分遮挡和非刚性变形。所提出的分层采样方法从后部集中的区域生成样本,以减少计算时间。该方法在许多具有遮挡和非刚性变形的具有挑战性的图像序列上进行了广泛的测试,证明了其在不同情况下的实时性和鲁棒性。

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