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» Discriminative Random Fields for Behavior Modeling
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CVPR
2008
IEEE
14 years 10 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
NIPS
2008
13 years 10 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
ICASSP
2007
IEEE
14 years 2 months ago
Context-Based Concept Fusion with Boosted Conditional Random Fields
The contextual relationships among different semantic concepts provide important information for automatic concept detection in images/videos. We propose a new context-based conce...
Wei Jiang, Shih-Fu Chang, Alexander C. Loui
ICASSP
2010
IEEE
13 years 8 months ago
Discriminative template extraction for direct modeling
This paper addresses the problem of developing appropriate features for use in direct modeling approaches to speech recognition, such as those based on Maximum Entropy models or S...
Shankar Shivappa, Patrick Nguyen, Geoffrey Zweig
ECCV
2008
Springer
14 years 10 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele