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Tracking, Learning & Detection of a real time objects in video stream plays a very crucial role in case of surveillance video. An object is defined by its position & extent in next frame. Efficiently designed object tracking systems can provide better efficiency but sometimes they fail due to loss of information caused by complex shapes, rapid motion and illumination changes. There are different types of algorithms that can be used like DNN,MOSSE, BOOSTING, MIL, MEDIANFLOW,TLD, KCF, CSRT. The proposed system uses Deep Neural Network (DNN) in order to detect an object. using Open CV trackers. This paper describes a method for tracking multiple objects and moving in real time of tracking in video stream. Initial results shows that the different object tracking methods have different properties with respect to number & trajectories of the objects


Multiple object tracking, TLD , KCF, Median Flow, CSRT

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How to Cite
Mr. Ankit Pandey, Mr. Parmatma Pandey, and Prof. Geetha Narayanan, “DETECTION-LEARNING-TRACKING OF MULTIPLE OBJECTS IN VIGILANCE VIDEO”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 5, p. 7, Jun. 2020.


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