Moving Object Detection for Night Surveillance
Yuan-Kai Wnag, Ching-Tang Fan · 2010
Traditional background subtraction methods perform poorly at night. In this paper, a robust method is proposed for automatic visual surveillance in low-light level environment which has quality problems of low brightness, low contrast and high-level noise. The novel method includes techniques of illumination compensation and illumination-invariant background subtraction to solve the low-quality problem in night surveillance. Experiments are conducted on several challenging videos captured with drastic illumination change at night. Experimental results demonstrate that the proposed approach significantly outperforms existing techniques for the extraction of moving objects at night.