Abstract

Vision is important in life; in earlier years many systems fail because of poor classification. Objects can be classified as living or man-made movable objects such as a human, vehicles, animals, floating clouds, and swaying trees in the field of computer vision. Many algorithms have been proposed for classification from the image of a video stream. For robust and accurate tracking, it also depends on a good classification algorithm that segments foregrounds from a background in a video stream. The goal of object classification is to extract useful information from images pinpointing between static and moving objects. In this paper, different types of classification algorithms are discussed, and tracking techniques are proposed in the field of computer vision. The goal of tracking is not achieved without the classification of objects.

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