Article ID Journal Published Year Pages File Type
532115 Pattern Recognition 2014 14 Pages PDF
Abstract

•Introduces Gravity Optimised Particle Filter (GOPF) to improve particle propagation.•GOPF introduces gravitational force in addition to weighted particles.•GOPF attracts particles towards peak of likelihood distribution to improve sampling.•Introduces a fast detection and labelling of hand features using convexity defects.•GOPF is incorporated in hand features tracking with a validation gate mechanism.

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.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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