Detecting persons on changing background

We need a reliable visual surveillance system that can work under various disturbances, such as changes of lighting and movements of background objects. We propose a method exploiting information over space and time. First, optical flow is computed, and then regions with uniform flow are extracted. The regions are hypothesized as parts of detection targets. Assuming that the targets move in constant directions at constant speeds, we predict a path of each region and vote it in the space-time cube. If enough number of votes support a particular path, the method reports the detection of the intruder. We have implemented this method using multiple DSP boards and constructed a system that works in real time. Experimental results show that the system can detect intruders walking with many objects moving in their backgrounds