Efficient shadow removal technique for tracking human objects

This paper deals with the shadow removal algorithm for tracking human object with the background subtraction and occlusion detection technique. This is implemented by initially considering a reference frame and using its background information. When a new object enters into the frame, the foreground image and background image are derived using the reference frame which was taken earlier as background image. Most of the times, the shadow from background information mixes with the foreground object hence results in intricate tracking process. The algorithm used involves modeling of the desired background as a reference model which is later used in background subtraction to produce foreground pixels which are the deviation of the current frame from the reference one. Here, morphological operations will be used for identifying and removing the shadow. The occlusion is one of the most common events in object tracking and centroid of each object are used for detecting the occlusion and identifying each object separately. Video sequences are captured and detected with the proposed algorithm.