Abstract:

Abstract Context. The implementation of video analytics functions in video surveillance systems makes it possible to increase the efficiency of these systems. One of the functions of these intelligent video surveillance systems is to detect dynamic objects in the surveillance sectors of video surveillance cameras. Existing methods of background subtractoin and object recognition have important disadvantages that limit their application in practice: under low contrast algorithms can not select an object from the background; some moving objects can be recognized as a background, algorithms critical to lighting conditions, and so on. Therefore, an important task is to develop and improve methods for detecting dynamic objects in video sequences.

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