Abstract
With the quick increase of video data, it is difficult for people to find the favorite video to watch quickly. The existing video summarization methods can do a favor for viewers. However, these methods mainly contain the very brief content from the start to the end of the whole video. Viewers may hardly be interested in scanning these kinds of summary videos, and they will want to know the interesting or exciting contents in a shorter time. In this paper, we propose a video summarization approach of powerful and attractive contents based on the extracted deep learning feature and implement our approach on One Class SVM (OCSVM). Extensive experiments demonstrate that our approach is able to extract the powerful and attractive contents effectively and performs well on generating attractive summary videos, and we can provide a benchmark of powerful content extraction at the same time.
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Acknowledgment
The authors wish to acknowledge the financial support from the Chinese Natural Science Foundation under the grant No 61373103.
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Liu, X., Song, X., Jiang, J. (2015). The Extraction of Powerful and Attractive Video Contents Based on One Class SVM. In: Ho, YS., Sang, J., Ro, Y., Kim, J., Wu, F. (eds) Advances in Multimedia Information Processing -- PCM 2015. PCM 2015. Lecture Notes in Computer Science(), vol 9314. Springer, Cham. https://doi.org/10.1007/978-3-319-24075-6_36
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DOI: https://doi.org/10.1007/978-3-319-24075-6_36
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