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ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
14 years 1 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
ICIP
2004
IEEE
14 years 8 months ago
Discovering meaningful multimedia patterns with audio-visual concepts and associated text
The work presents the first effort to automatically annotate the semantic meanings of temporal video patterns obtained through unsupervised discovery processes. This problem is in...
Lexing Xie, Lyndon S. Kennedy, Shih-Fu Chang, Ajay...
ICIP
2003
IEEE
14 years 8 months ago
Feature selection for unsupervised discovery of statistical temporal structures in video
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang...
CVPR
2012
IEEE
11 years 9 months ago
Learning latent temporal structure for complex event detection
In this paper, we tackle the problem of understanding the temporal structure of complex events in highly varying videos obtained from the Internet. Towards this goal, we utilize a...
Kevin Tang, Fei-Fei Li, Daphne Koller
ECAI
2004
Springer
14 years 14 days ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana