Gravity optimised particle filter for hand tracking
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, impr...
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| Format: | Article |
| Language: | English |
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Elsevier
2014
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| Online Access: | http://irep.iium.edu.my/35420/ http://irep.iium.edu.my/35420/1/Gravity_Optimised_Particle_Filter_for_Hand_Tracking.pdf |
| _version_ | 1848781051592179712 |
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| author | Morshidi, Malik Arman Tjahjadi, Tardi |
| author_facet | Morshidi, Malik Arman Tjahjadi, Tardi |
| author_sort | Morshidi, Malik Arman |
| building | IIUM Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T15:43:25Z |
| format | Article |
| id | iium-35420 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:43:25Z |
| publishDate | 2014 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-354202018-06-25T00:27:33Z http://irep.iium.edu.my/35420/ Gravity optimised particle filter for hand tracking Morshidi, Malik Arman Tjahjadi, Tardi Q300 Cybernetics T Technology (General) 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. Elsevier 2014-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/35420/1/Gravity_Optimised_Particle_Filter_for_Hand_Tracking.pdf Morshidi, Malik Arman and Tjahjadi, Tardi (2014) Gravity optimised particle filter for hand tracking. Pattern Recognition Letters, 47 (1). pp. 194-207. ISSN 01678655 http://dx.doi.org/10.1016/j.patcog.2013.06.032 doi:10.1016/j.patcog.2013.06.032 |
| spellingShingle | Q300 Cybernetics T Technology (General) Morshidi, Malik Arman Tjahjadi, Tardi Gravity optimised particle filter for hand tracking |
| title | Gravity optimised particle filter for hand tracking |
| title_full | Gravity optimised particle filter for hand tracking |
| title_fullStr | Gravity optimised particle filter for hand tracking |
| title_full_unstemmed | Gravity optimised particle filter for hand tracking |
| title_short | Gravity optimised particle filter for hand tracking |
| title_sort | gravity optimised particle filter for hand tracking |
| topic | Q300 Cybernetics T Technology (General) |
| url | http://irep.iium.edu.my/35420/ http://irep.iium.edu.my/35420/ http://irep.iium.edu.my/35420/ http://irep.iium.edu.my/35420/1/Gravity_Optimised_Particle_Filter_for_Hand_Tracking.pdf |