A novel video summarization method for multi-intensity illuminated infrared videos

In nighttime video surveillance, proper illumination plays a key role for the image quality. For ordinary IR-illuminators with fixed intensity, faraway objects are often hard to identify due to insufficient illumination while nearby objects may suffer from over-exposure, resulting in image foreground/background of poor quality. In this paper we proposed a novel video summarization method which utilizes a novel multi-intensity IR-illuminator to generate images of human activities with different illumination levels. By adopting GMM-based foreground extraction procedure for images acquired for each illumination level, foreground objects with most plausible quality can be selected and merged with a preselected representation for still background. The result brings out a reasonable video summary for moving foreground, which is generally unachievable for nighttime surveillance videos.