Abstract
Detect moving objects from a video sequence is a fundamental and critical task in many computer vision application. For security forewarning demand of the high-speed railway transport hub video surveillance system, we need a stable, fast and accurate moving object detection method to promptly find the congestion of passenger flow and other dangerous in hub. Through the comparative study on moving object detection, we select average background model to build background and gray area division to improve the processing speed of background modeling. Experiment result shows our method is suitable for high-speed railway transport hub video surveillance.
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