Feature integration for adaptive visual tracking in a particle filtering framework
Publish place: 14th annual International CSI Computer Conference
Publish Year: 1388
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CSICC14_054
تاریخ نمایه سازی: 24 خرداد 1388
Abstract:
In this paper we propose a new integration method for multi-feature object tracking in a particle filter framework. We divide particles into separate clusters. All particles within a cluster measure a specific feature. The number of particles within a cluster is in proportion to the reliability of associated feature. We do a compensation stage which neutralizes the effect of particles weights mean within a cluster. Compensation stage balances the concentration of particles around local maximal. So, particles are distributed more effectively in the scene. Proposed method provides both effective hypothesis generation and effective evaluation of hypothesis. Experimental results over a set of real-world sequences demonstrate better performance of our method compared to the common methods of feature integration.
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Authors
M Komeili
Dept of Electrical Engineering, Tarbiat Modarres University
N Armanfard
Dept of Electrical Engineering, Tarbiat Modarres University