Abstract
A video is considered as high dimensional data which is tedious to process. Shot detection and key frame selection are activities to reduce redundant data from a video and make it presentable in few images. Researchers have worked in this area diligently. Basic shot detection schemes provide shot boundaries in a video sequence and key frames are selected based on each shot. Usually in video clips, shots repeat after one another, in that case the basic shot detection scheme gives redundant key frames from same video. In this work, we have proposed a hierarchical shot detection and key frames selection scheme which reduce a considerable amount of redundant key frames. For temporal analysis and abrupt transformation detection, color histogram has been used. After shot detection, spatial analysis has been done using local features. Local binary patterns have been utilized for local feature extraction. The proposed scheme is applied to three video sequences of news video, movie clip and tv-advertisement video.
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Verma, M., Raman, B. (2017). A Hierarchical Shot Boundary Detection Algorithm Using Global and Local Features. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_35
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DOI: https://doi.org/10.1007/978-981-10-2107-7_35
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