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3D TRACKING OF PEOPLE WITH RAO-BLACKWELLIZED PARTICLE FILTERS
Date
2014-04-25
Author
Topcu, Osman
Orguner, Umut
Alatan, Abdullah Aydın
ERCAN, ALİ ÖZER
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Visual tracking has an important place among computer vision applications. Visual tracking with particle filters is a well-known methodology. The performance of particle filters is dependent on efficient sampling of the state space, which in turn, is dependent on number of particles. In this paper, Rao-Blackwell technique is applied to particle filters to improve sampling efficiency. Both algorithms are applied to people tracking problem. Under the same circumstances, the resulting algorithm is demonstrated to perform better than the original algorithm via experiments on the PETS2009 benchmark dataset.
Subject Keywords
Visual Tracking
,
Rao-Blackwellization
,
Marginalization
,
Occlusion
,
Particle Filter
,
Multi-Camera
URI
https://hdl.handle.net/11511/55553
Conference Name
22nd IEEE Signal Processing and Communications Applications Conference (SIU)
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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O. Topcu, U. Orguner, A. A. Alatan, and A. Ö. ERCAN, “3D TRACKING OF PEOPLE WITH RAO-BLACKWELLIZED PARTICLE FILTERS,” presented at the 22nd IEEE Signal Processing and Communications Applications Conference (SIU), Karadeniz Teknik Univ, Trabzon, TURKEY, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55553.