Robust detection & tracking of object by particle filter using color information

Abstract

Robust visual tracking of object over extended image sequence is one of the most challenging problems in computer vision. Effective solutions to this problem are crucial for applications such as smart video surveillance, intelligent human machine interaction, machine vision and robotics. Most tracking method can be classified into two major types, namely, probabilistic filtering algorithms and deterministic localization algorithms. In this paper some improvement in color based tracking has been proposed and employed to track a moving object. The object state has been taken as the object position, speed, size, object size scale and the appearance condition of the object. The target model update condition and adaptive likelihood had been calculated to ensure the proper tracking of an object. From the simulation results it is observed that the proposed algorithm is a suitable and efficient methodology for object tracking in many challenging situations.