3D TRACKING OF PEOPLE WITH RAO-BLACKWELLIZED PARTICLE FILTERS

Date

2014-04-25

Author

Topcu, Osman
Orguner, Umut
Alatan, Abdullah Aydın
ERCAN, ALİ ÖZER

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This work is licensed under a 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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Citation Formats

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.