Video Segmentation for Moving Object Detection & Tracking- a Review

ABSTRACT The objective of our paper is to review the contemporary video segmentation & tracking methods, organize them into different categories, and identify new learning’s. Object detection and tracking, in general, is a stimulating problem. The detection of moving object is important in many tasks, such as video surveillance and moving object tracking. The design of a video surveillance system is directed on automatic identification of events of interest, especially on tracking and classification of moving objects. Complications in tracking objects can arise due to unexpected object motion, changing appearance patterns of both the object and the scene, non-rigid object edifices, object-to-object and to scene obstructions, and camera motion. Tracking is usually performed in the context of higher-level applications that require the location and/or shape of the object in every frame. Typically, assumptions are made to constrain the tracking problem in the context of a particular application. In this investigation, we categorize the tracking methods on the basis of the object and motion representations used, afford thorough descriptions of representative methods in each class. Furthermore, we deliberate the important concerns related to tracking including the use of appropriate image features, selection of motion representations, and detection of objects.