Abstract
Keyframe extraction is an essential task in many video analysis applications such as video summarization, video classification, video indexing and retrieval. In this paper, a method of extracting keyframes from the shots using bitwise XOR dissimilarity has been proposed. The task of segmenting continuous video into shots and selection of key frames from segmented shots has been addressed. The above task has been accomplished through a feature extraction technique, based on bitwise XOR operation between consecutive gray scale frames of the video. Thresholding mechanism is employed to segment the videos into shots. Dissimilarity matrix is constructed to select a representative keyframe from every shot of a video sequence. The proposed shot boundary detection and keyframe extraction approach is implemented and evaluated on a subset of TRECVID 2001 data set. The proposed approach outperform other contemporary approaches in terms of efficiency and accuracy. Also, the experimental results on the data set have demonstrated the efficacy of the proposed keyframe extraction technique in terms of fidelity measure.
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B.S., R., H.S., N. (2017). Shot-Based Keyframe Extraction Using Bitwise-XOR Dissimilarity Approach. In: Santosh, K., Hangarge, M., Bevilacqua, V., Negi, A. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2016. Communications in Computer and Information Science, vol 709. Springer, Singapore. https://doi.org/10.1007/978-981-10-4859-3_28
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DOI: https://doi.org/10.1007/978-981-10-4859-3_28
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