?In this project, real time?object tracking is a challenging task due to?dynamic tracking?environment?and different limiting parameters like view point,anthropometric?variation, dimensions of an object, cluttered?background, camera motions, occlusion etc.
In this project,?we?have developed?new object detection and tracking algorithm?which makes use of optical flow in conjunction with motion?vector estimation for object detection and tracking in a sequence?of frames.
The optical flow gives valuable information about the?object movement even if no quantitative parameters are?computed .??
optical flow??is the pattern of apparent?motion??of objects, surfaces, and edges in a visual scene caused by the?relative motion??between an observer and a scene.?The motion vector estimation technique can provide?an estimation of object position from consecutive frames which?increases the accuracy?of this algorithm and helps to provide?robust result irrespective?of image blur and cluttered?background.
The use of?median filter with this?algorithm makes?it more robust in the presence of noise. The developed algorithm?is applied to wide range of standard and real time datasets with?different illumination (indoor and outdoor), object speed etc.
The?obtained results indicates that the developed algorithm over?performs over conventional methods and state of art methods of video?tracking