Paper
18 December 2003 Home video summarization by shot characteristics and user's feedback
Author Affiliations +
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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nagul Cooharojananone, Supatana Auethavekiat, and Kiyoharu Aizawa "Home video summarization by shot characteristics and user's feedback", Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); https://doi.org/10.1117/12.526556
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KEYWORDS
Video

Nanoimprint lithography

Detection and tracking algorithms

Cameras

Data storage

Edge detection

Electrical engineering

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