Abstract
In this Letter, a new algorithm to reduce false positive in video surveillance by integrating depth using laser range finder with conventional camera is proposed. Typical video surveillance detects foreground objects by background model using only image. Background model is updated using brightness value on image so that it has difficulty in modelling diverse variations caused by illumination changes or scene structure variations. Inherently, there could be many false positives. Hypothesis generation and verification paradigm is adopted by integrating laser range finder with camera on video surveillance. Conventional background updating algorithm is used for generating foreground objects. They are verified by depth value provided by laser range finder. Rotating 2D laser range finder for targeting and generation of look-up table is used. Experimental results show that proposed algorithm can reduce false positives in video surveillance.
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