IMPLEMENTATION OF REAL TIME OBJECT DETECTION & TRACKING

Abstract

In this project we present an approach to develop a real-time object tracking system using a static camera to grab the video frames and track an object. The work presents the concepts of histogram matching and absolute frame subtraction to implement a robust automated object tracking system. Once the object is detected it is tracked using discrete Kalman filter technique. The histogram matching algorithm helps to identify when the object enters the viewing range of the camera and the absolute frame subtraction gives better results even with low quality videos. Such a tracking system can be used in surveillance applications and proves to be cost effective. A simulink model is also developed for object tracking for real time video