Semantic video clustering across sources using bipartite spectral clustering

@article{Zhang2004SemanticVC,
  title={Semantic video clustering across sources using bipartite spectral clustering},
  author={DongQing Zhang and Ching-Yung Lin and Shih-Fu Chang and John R. Smith},
  journal={2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763)},
  year={2004},
  volume={1},
  pages={117-120 Vol.1}
}
Data clustering is an important technique for visual data management. Most previous work focuses on clustering video data within single sources. We address the problem of clustering across sources, and propose novel spectral clustering algorithms for multisource clustering problems. Spectral clustering is a new discriminative method realizing clustering by partitioning data graphs. We represent multi-source data as bipartite or K-partite graphs, and investigate the spectral clustering algorithm… CONTINUE READING
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