Gravity optimised particle filter for hand tracking
Gravity optimised particle filter for hand tracking
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DOI：
10.1016/j.patcog.2013.06.032
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Malik Morshidi;T. Tjahjadi
中科院分区：
文献类型：
--
作者：
Malik Morshidi;T. Tjahjadi
本文提出了一种重力优化粒子滤波器（GOPF），其中每个粒子的重力大小与其权重成正比。GOPF吸引附近的粒子并复制新的粒子，就好像将粒子移向似然分布的峰值，从而提高了采样效率。GOPF被纳入到一个技术的手特征跟踪。提出了一种基于凸度缺陷的手部特征快速检测和标记方法。实验结果表明，GOPF优于标准粒子滤波器及其变体，以及最先进的CamShift引导粒子滤波器使用显着减少的粒子数量。
This paper presents a gravity optimised particle filter (GOPF) where the magnitude of the gravitational force for every particle is proportional to its weight. GOPF attracts nearby particles and replicates new particles as if moving the particles towards the peak of the likelihood distribution, improving the sampling efficiency. GOPF is incorporated into a technique for hand features tracking. A fast approach to hand features detection and labelling using convexity defects is also presented. Experimental results show that GOPF outperforms the standard particle filter and its variants, as well as state-of-the-art CamShift guided particle filter using a significantly reduced number of particles.