Search

The paper presents a particle filter for integrated detection and tracking of multiple objects in image sequences, using color as the observation feature. The color based feature has been found useful when dealing with non-rigid object deformations, partial occlusions, rapidly changing dynamics and complex backgrounds. The problem of joint detection and tracking is formulated as a hybrid valued sequential state estimation problem, incorporating a discrete variable which represents the number of existing objects. The solution is implemented in the form of a particle filter. The performance of the proposed algorithm is evaluated on various real-world video sequences with objects entering and leaving the scene., Anglais

Recent works have shown that the particle filter using color as observation feature is a powerful technique for tracking deformable objects in image sequences with complex backgrounds. This paper presents a hybrid valued sequential state estimation algorithm, and its particle filter-based solution, that extends the standard color particle filter in two ways. Firstly, track initialization is embedded in the particle filter without relying on an external target detection algorithm. Secondly, the algorithm is able to track multiple objects sharing the same color description. We evaluate the performance of the proposed filter on various real-world video sequences with appearing and disappearing targets., Anglais