基于精英粒子Mean Shift的粒子滤波手部跟踪

S. Zhong, Fei Hao
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引用次数: 18

摘要

提出了一种改进的粒子滤波方法,用于视频序列中的实时手部跟踪。在该方法中,我们将精英粒子的均值漂移过程融入到传统的粒子滤波中,以达到提高跟踪效率的目的。基于观测模型,从权重较高的粒子中选择精英粒子。与传统的粒子滤波相比,该方法可以显著提高跟踪性能,并降低计算量。手部跟踪实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hand Tracking by Particle Filtering with Elite Particles Mean Shift
This paper presents an improved particle filtering for hand tracking in a video sequence in real time. In this method, we incorporate mean shift process of elite particles into conventional particle filtering for hand tacking which aims to improve the tracking efficiency. The elite particles are chosen from the particles with higher weights based on observation model. The proposed method can significantly improve the tracking performance, as well as reducing the computational cost compared to conventional particle filtering. Experiments result of the hand tracking show the effectiveness of proposed method.
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