Morshidi, Malik Arman and Tjahjadi, Tardi (2014) Gravity optimised particle filter for hand tracking. Pattern Recognition Letters, 47 (1). pp. 194-207. ISSN 01678655
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Abstract
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.
Item Type: | Article (Journal) |
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Additional Information: | 4570/35420 |
Uncontrolled Keywords: | Particle filter, Articulated hand tracking, Finger movement, Gravity, Convexity defects, CamShift |
Subjects: | Q Science > Q Science (General) > Q300 Cybernetics T Technology > T Technology (General) |
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): | Kulliyyah of Engineering > Department of Electrical and Computer Engineering |
Depositing User: | Dr Malik Arman Morshidi |
Date Deposited: | 06 Feb 2014 16:18 |
Last Modified: | 25 Jun 2018 08:27 |
URI: | http://irep.iium.edu.my/id/eprint/35420 |
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