Paper
1 January 2001 Video shot grouping using best-first model merging
Li Zhao, Wei Qi, Yi-Jin Wang, Shi-Qiang Yang, HongJiang Zhang
Author Affiliations +
Proceedings Volume 4315, Storage and Retrieval for Media Databases 2001; (2001) https://doi.org/10.1117/12.410935
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States
Abstract
For more efficiently organizing, browsing, and retrieving digital video, it is important to extract video structure information at both scene and shot levels. This paper present an effective approach to video scene segmentation based on probabilistic model merging. In our proposed method, we regard the shots in video sequence as hidden state variable and use probabilistic clustering to get the best clustering performance. The experimental results show that our method produces reasonable clustering results based on the visual content. A project named HomeVideo is introduced to show the application of the proposed method for personal video materials management.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Li Zhao, Wei Qi, Yi-Jin Wang, Shi-Qiang Yang, and HongJiang Zhang "Video shot grouping using best-first model merging", Proc. SPIE 4315, Storage and Retrieval for Media Databases 2001, (1 January 2001); https://doi.org/10.1117/12.410935
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Cited by 29 scholarly publications.
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KEYWORDS
Video

Data modeling

Semantic video

Visualization

Video processing

Performance modeling

Algorithm development

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