Entropy metrics used for video summarization
SCCG '02 Proceedings of the 18th spring conference on Computer graphics
Video summarisation: A conceptual framework and survey of the state of the art
Journal of Visual Communication and Image Representation
Bayesian unsupervised word segmentation with nested Pitman-Yor language modeling
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
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This paper provides a novel summarization method for drive videos using driving behavior, such as driver maneuvers and vehicle reaction, recorded simultaneously alongside video. We segmented the driving behavior into chunks via an unsupervised manner and summarized the drive videos using the chunks, i.e., the switching points of the chunks were emphasized and the middle of the chunks were compressed. As the result of subjective evaluation, we found that the chunks were more consistent with human-recognized driving context than the image-based method and that the summarized video was more suitable for reviewing entire driving scenes, i.e., our method achieved an efficient summarization.