Real-time implementation of object detection and tracking on DSP for video surveillance applications

In the recent years, object detection and tracking has become an integral part of various applications such as Surveillance system, Vehicle navigation, and autonomous robot navigation. Especially in the field of surveillance system it has gained greater significance than ever before due to the recent terror activities taking place all over the world. Many efforts have been made to make the system automated in order to decrease the complexity and to increase the ease with which it can be implemented. The paper describes the implementation of Object Detection and Tracking for the surveillance system on DSP board Embest Dev Kit 8500D using Modified Background Subtraction algorithm. The camera used in the system, Microsoft LifeCam HD 3000 camera, operates at a speed of 30fps. The DSP board acts as a standalone system with Linux based Angstrom Operating System (OS) installed in it and it is programmed in C++ language integrated with OpenCV library. Contrary to the conventional Background Subtraction algorithm where a fixed reference frame is subtracted from incoming frame, Frame Differencing technique is used in this paper in which two consecutive frames are subtracted from one another to remove the stationary background. The design is successfully implemented to detect and track the object with a minimum time delay.