Abstract
Video summarization is a procedure to reduce the size of the original video without affecting vital information presented by the video. This paper presents an innovative video summarization technique based on inter-frame information variation. Similar group of frames are identified based on inter-frame information similarity. Key frames of a group are selected using disturbance ratio (DR), which is derived by measuring the ratio of information changes between consecutive frames of a group. The frames in the summarized video are selected by considering continuation in understanding the message carried out by the video. Higher priority is given to the frames which have higher information changes, and no-repetition to reduce the redundant areas in the summarized video. The higher information changes in the video frames are detected based on the DR measure of the group and this makes our algorithm adaptive in respect to the information content of the source video. The results show the effectiveness of the proposed technique compared to the related research works.
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Maity, S., Chakrabarti, A., Bhattacharjee, D. (2011). An Innovative Technique for Adaptive Video Summarization. In: Venugopal, K.R., Patnaik, L.M. (eds) Computer Networks and Intelligent Computing. ICIP 2011. Communications in Computer and Information Science, vol 157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22786-8_75
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DOI: https://doi.org/10.1007/978-3-642-22786-8_75
Publisher Name: Springer, Berlin, Heidelberg
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