Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
10-2004
Abstract
This paper proposes a new approach and algorithm for the similarity measure of video clips. The similarity is mainly based on two bipartite graph matching algorithms: maximum matching (MM) and optimal matching (OM). MM is able to rapidly filter irrelevant video clips, while OM is capable of ranking the similarity of clips according to the visual and granularity factors. Based on MM and OM, a hierarchical video retrieval framework is constructed for the approximate matching of video clips. To allow the matching between a query and a long video, an online clip segmentation algorithm is also proposed to rapidly locate candidate clips for similarity measure. The validity of the retrieval framework is theoretically proved and empirically verified on a video database of 21 hours.
Keywords
Clip-based similarity, Hierarchical video retrieval
Discipline
Databases and Information Systems | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval, New York, October 15-16
First Page
53
Last Page
60
ISBN
9781581139402
Identifier
10.1145/1026711.1026721
Publisher
ACM
City or Country
New York
Citation
PENG, Yuxin and NGO, Chong-wah.
Clip-based similarity measure for hierarchical video retrieval. (2004). Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval, New York, October 15-16. 53-60.
Available at: https://ink.library.smu.edu.sg/sis_research/6507
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Databases and Information Systems Commons, Graphics and Human Computer Interfaces Commons