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A Particle Filtering For 3D Human Hand Tracking

机译:用于3D人体手部跟踪的粒子过滤

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摘要

A novel sampling method is put forward in this paper. Firstly, under specific human-computer conditions, both cognitive psychology features of operators and motion features of the operators' hands are studied, upon which a basic assumption is made. Then, a sampling algorithm is put forward. Finally, in order to demonstrate validity and performance of our algorithm, a great deal of experiments is completed. By using fewer particles, compared with conventional particle filtering, the approach presented in this paper may achieve better tracking precision. In forms of both the theoretical analysis and a great deal of experimental results from real video data, just a few particles are needed to describe post probability distribution of state variables without reducing the tracking precision by our dimensionality reduction method.
机译:提出了一种新颖的采样方法。首先,在特定的人机环境下,研究了操作者的认知心理特征和操作者手的运动特征,并以此为基本假设。然后,提出了一种采样算法。最后,为了证明我们算法的有效性和性能,完成了大量实验。与传统的粒子滤波相比,通过使用更少的粒子,本文提出的方法可以实现更好的跟踪精度。在理论分析和大量来自真实视频数据的实验结果的形式中,仅需少量粒子即可描述状态变量的事后概率分布,而无需通过我们的降维方法来降低跟踪精度。

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