Multiple Objects Tracking using CAMshift Algorithm in Open CV

Abstract

These paper reviews tracking of multiple moving objects with CAMshift algorithm in OpenCV. In many other cases CAMshift considered a feature of tracked object which need to track in video stream. Many times CAMshift algorithm used for face tracking. But in our paper we implement approach of CAMshift algorithm which is capable of track multiple moving objects in video stream. In our paper, we have not considered any feature of object to be tracked. Here first Reference frame is selected by user and further continuously updated Binary foreground pixels are given as an argument to CAMshift, for locating location of desired objects in each frame. Motion contour detection is achieved. By providing overlap threshold criteria in scope of CAMshift algorithm multiple objects are tracked in consecutive video frames and ellipse is getting drawn around each tracked object. We proved, CAMshift algorithm can be implemented in effective manner for multiple objects tracking in video stream.

Particle filter and camshift approach for motion detection: a comparative study

“…CAMShift algorithm is frequently used for object tracking in video surveillance, which has a good realtime performance. Firstly, the moving object can be obtained by background subtraction and frame differences method, then the location of extracted moving target will be taken as the initial search window for the CAMShift algorithm, and finally the automatic tracking of the moving target can be realized [3].…”

“…Steps for CAMShift Algorithm: The CAMShift algorithm can be summarized in the following steps [3]: (1) Initialize the search window. (2) Calculate the color probability distribution of the search window (back projection).…”