One of the most crucial aspects to be taken into consideration during the development of visual surveillance system is the need to inform the human operator about any unusual situation happening. The paper presents an idea of real-time video stream analysis which leads to the detection and tracking of suspicious objects that have been left unattended. The mathematical principles related to background model creation and detection tuning are included. Developed algorithm has been implemented as a working model involving OpenCV library and tested on benchmark data taken from real visual surveillance system.
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