The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A user attention model for video summarization
Abstract
Automatic generation of video summarization is one of the key techniques in video management and browsing. In this paper, we present a generic framework of video summarization based on the modeling of viewer's attention. Without fully semantic understanding of video content, this framework takes advantage of computational attention models and eliminates the needs of complex heuristic rules in video summarization. A set of methods of audio-visual attention model features are proposed and presented. The experimental evaluations indicate that the computational attention based approach is an effective alternative to video semantic analysis for video summarization.
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Citations
Cites
Computational modelling of visual attention
Itti, L., & Koch, C. (2001) · Nature Reviews Neuroscience · doi:10.1038/35058500 · Cited by 4,733
Cited by
Contrast-based image attention analysis by using fuzzy growing
Ma, Y.-F., & Zhang, H.-J. (2003) · Proceedings of the eleventh ACM international conference on Multimedia · doi:10.1145/957013.957094 · Cited by 965
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Metadata
- Authors
- Ma, Y.-F., Lu, L., Zhang, H.-J., & Li, M.
- Venue
- Proceedings of the tenth ACM international conference on Multimedia
- Publisher
- ACM
- Published
- 2002-12
- Pages
- 533-542
- OpenAlex
- W2006180404
- Cited by
- 551
- References
- 1
- FWCI
- 18.70
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Ma, Y.-F., Lu, L., Zhang, H.-J., & Li, M. (2002). A user attention model for video summarization. Proceedings of the tenth ACM international conference on Multimedia. https://doi.org/10.1145/641007.641116
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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