Abstract
In this paper a novel method for video summarization is presented, which uses a color-based feature extraction technique and a graph-based clustering technique. One major advantage of this method is that it is parameter-free, that is, we do not need to define neither the number of shots or a consecutive-frames dissimilarity threshold. The results have shown that the method is both effective and efficient in processing videos containing several thousands of frames, obtaining very meaningful summaries in a quick way.
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Castelo-Fernández, C., Calderón-Ruiz, G. (2015). Automatic Video Summarization Using the Optimum-Path Forest Unsupervised Classifier. In: Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Science(), vol 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_91
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DOI: https://doi.org/10.1007/978-3-319-25751-8_91
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