Object tracking in a multi camera environment

Tracking objects in multi camera environments is an important requirement for video surveillance applications. A new active particle filter based tracking technique is presented, where objects are tracked across different cameras using a reduced number of particles. In order to cope with sudden colour and scale changes, a variable standard deviation value for spreading the particles is proposed. As the object moves from one scene to another, the number of particles along with the spread value is increased to minimize any effect of scale and colour change. The technique has been tested on live feeds from two different cameras and with scenes from the PETS dataset. The results have been compared with standard particle filtering techniques. It was found that not only did the proposed method result in almost similar tracking results but there is a 70% reduction in computational cost.