Object tracking is considered to be a key and important task in intelligent video surveillance system. Many algorithms have been developed for object tracking, such as Mean-shift, Kalman-filter, and particle-filter algorithm. However, utilizing only one of these algorithms is considered inefficient because all single algorithms have their limitations. We proposed an improved algorithm which combines these three traditional algorithms to cover each algorithms drawbacks. Moreover we also utilized a combination of two features which are color histogram and texture to improve the tracking performance. The experimental results show that the proposed method is robust to cope with several tracking problems such as illumination variation, non-rigid deformation, non-linear movement, similar color interference, and occlusion. Furthermore, our proposed algorithm show better results compare to other comparator algorithms

Visual Object Tracking; multi features; Meanshift; Particle-Kalman Filter

• Kanyadian Idananta, S.Kom., M.TI

• Irene Anindaputri Iswanto, S.Kom., M.Sc.Eng.