VISUAL ATTENTION BASED KEYFRAMES EXTRACTION AND VIDEO SUMMARIZATION

Recent developments in digital video and drastic increase of internet use have increased the amount of people searching and watching videos online. In order to make the search of the videos easy, Summary of the video may be provided along with each video. The video summary provided thus should be effective so that the user would come to know the content of the video without having to watch it fully. The summary produced should consists of the key frames that effectively express the content and context of the video. This work suggests a method to extract key frames which express most of the information in the video. This is achieved by quantifying Visual attention each frame commands. Visual attention of each frame is quantified using a descriptor called Attention quantifier. This quantification of visual attention is based on the human attention mechanism that indicates color conspicuousness and the motion involved seek more attention. So based on the color conspicuousness and the motion involved each frame is given a Attention parameter. Based on the attention quantifier value the key frames are extracted and are summarized adaptively. This framework suggests a method to produces meaningful video summary.