Video Summarization for Multi-intensity Illuminated Infrared Videos

• Main Authors: Lu, Yi-Chun, 魯怡君
• Other Authors: Chuang, Jen-Hui
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/37670354304076414799

碩士 === 國立交通大學 === 多媒體工程研究所 === 101 === 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 be identified due to insufficient illumination while nearby objects may suffer from over-exposure, resulting in image foreground/background of poor quality. In this thesis we proposed a novel video summarization method which utilizes a multi-intensity IR-illuminator to generate images of human activities with different illumination levels. First, a GMM-based foreground extraction procedure is adopted for images acquired under each illumination level. With quality assessment of the outcome of such procedure, the system than selects visually most plausible foreground regions from different illumination levels to generate a set of new input data. Finally, an automatic video summary method is developed to identify key frames for these data and merge them 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.