Feature integration for adaptive visual tracking in a particle filtering framework
عنوان مقاله: Feature integration for adaptive visual tracking in a particle filtering framework
شناسه ملی مقاله: CSICC14_054
منتشر شده در چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران در سال 1388
شناسه ملی مقاله: CSICC14_054
منتشر شده در چهاردهمین کنفرانس بین المللی سالانه انجمن کامپیوتر ایران در سال 1388
مشخصات نویسندگان مقاله:
M Komeili - Dept of Electrical Engineering, Tarbiat Modarres University
N Armanfard - Dept of Electrical Engineering, Tarbiat Modarres University
M Valizadeh
E Kabir
خلاصه مقاله:
M Komeili - Dept of Electrical Engineering, Tarbiat Modarres University
N Armanfard - Dept of Electrical Engineering, Tarbiat Modarres University
M Valizadeh
E Kabir
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.
کلمات کلیدی: feature combination, feature reliability, object tracking, particle filter, video sequence
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/73020/