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Proceedings Paper

Home video summarization by shot characteristics and user's feedback
Author(s): Nagul Cooharojananone; Supatana Auethavekiat; Kiyoharu Aizawa
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Paper Abstract

In this paper, we propose a home video summarization by representing a group of Representative frames (R-frames). The number of R-frames depends on shot characteristics which is shot duration and shot motion activity. For each shot, we apply an adaptive sub-sampling algorithm to extract the R-frames that contain only the high frame difference. When events of shots are not related to each other (One tape contains many events), it is desired to retrieve more information from more shots. Our algorithm allows users to select the number of shots appearing in the summarized video which give an optional way to understand the original sequence. In our experiments, we summarize video into variable number of shot appearing in the summary and evaluate the summary by users's subjective evaluations. We also summarize the home video by user's feedback. The user is asked to select the extracted R-frames as a training data. We apply the Support Vector Machine algorithm (SVM) to train and classify. The result from user's feedback shows that SVM retrieves the frames according to the user's desired.

Paper Details

Date Published: 18 December 2003
PDF: 8 pages
Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); doi: 10.1117/12.526556
Show Author Affiliations
Nagul Cooharojananone, Univ. of Tokyo (Japan)
Supatana Auethavekiat, Univ. of Tokyo (Japan)
Kiyoharu Aizawa, Univ. of Tokyo (Japan)


Published in SPIE Proceedings Vol. 5307:
Storage and Retrieval Methods and Applications for Multimedia 2004
Minerva M. Yeung; Rainer W. Lienhart; Chung-Sheng Li, Editor(s)

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