Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang Sun  Home/Search
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Abstract: Structure elements in a time sequence are repetitive segments that bear consistent deterministic or stochastic characteristics. While most existing work in detecting structures follow a supervised paradigm, we propose a fully unsupervised statistical solution in this paper. We present a unified approach to structure discovery from long video sequences as simultaneously finding the statistical descriptions of structure and locating segments that matches the descriptions. We model the multilevel... (Update)
Context of citations to this paper: More
...a post processing stage. Unsupervised discovery of structures have been applied to gene motif discovery and web stat mining (see reviews in [4]) Only a few instances has been explored for video. Clustering techniques are used on the key frames of shots [5] to discover the...
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BibTeX entry: (Update)
L. Xie, S.-F. Chang, A. Divakaran, and H. Sun, "Learning hierarchical hidden Markov models for video structure discovery, " Tech. Rep. 2002-006, ADVENT Group, Columbia Univ., http://www.ee.columbia.edu/dvmm/, December 2002. http://citeseer.ist.psu.edu/xie02learning.html More
@misc{ xie02learning,
author = "L. Xie and S. Chang and A. Divakaran and H. Sun",
title = "Learning hierarchical hidden Markov models for video structure discovery",
text = "L. Xie, S.-F. Chang, A. Divakaran, and H. Sun, Learning hierarchical hidden
Markov models for video structure discovery, Tech. Rep. 2002-006, ADVENT
Group, Columbia Univ., http://www.ee.columbia.edu/dvmm/, December 2002.",
year = "2002",
url = "citeseer.ist.psu.edu/xie02learning.html" }
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