Gravity optimised particle filter for hand tracking

PATTERN RECOGNITION

卷:47

Article

Morshidi, Malik¹  Tjahjadi, Tardi¹ 

[1] Univ Warwick, Sch Engn, Coventry CV4 7AL, W Midlands, England

关键词: Particle filter;    Articulated hand tracking;    Finger movement;    Gravity;    Convexity defects;    CamShift;   

DOI  :  10.1016/j.patcog.2013.06.032

来源: Elsevier

【 摘 要 】

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. (C) 2013 Elsevier Ltd. All rights reserved.

【 授权许可】

Free