Abstract

------------------------------------------------ABSTRACT---------------------------------------------------------Object detection and tracking are the tasks that are important and challenging in various computer vision applications such as surveillance, vehicle navigation, and autonomous robot navigation. Video surveillance works in a dynamic environment, especially for humans and vehicles. It is a technology helpful in fighting against terrorism, crime, public safety and for efficient management of traffic. Detection of moving objects from a video is important for object detection, target tracking, and understanding behaviour in video surveillance. Tracking of stationary foreground regions is one of the most important requirements for surveillance systems based on the tracking of abandoned or stolen objects or parked vehicles. To detect stationary foreground objects, the use of Object tracking techniques is the most popular choice. The objective of this paper is to highlight the various techniques of object tracking. This paper shows how one can simplify tracking by imposing constraints on the motion or appearance of objects. Prior knowledge about the number and the size of objects, or the object appearance and shape helps to simplify the problem. Numerous approaches for object tracking have been discussed.

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