Description

Video Tracking using Optical Flow

          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

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