Multiple human object tracking using background subtraction and shadow removal techniques

The main objective of this paper is to develop multiple human object tracking approach based on motion estimation and detection, background subtraction, shadow removal and occlusion detection. A reference frame is initially used and considered as background information. While a new object enters into the frame, the foreground information and background information are identified using the reference frame as background model. Most of the times, the shadow of the background information is merged with the foreground object and makes the tracking process a complex one. In the approach, morphological operations are used for identifying and removed the shadow. The occlusion is one of the most common events in object tracking and object centroid of each object is used for detecting the occlusion and identifying each object separately. Video sequences have been captured in the laboratory and tested with the proposed algorithm. The algorithm works efficiently in the event of occlusion in the video sequences.