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» A Markov Random Field Model for Automatic Speech Recognition
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CVPR
2011
IEEE
13 years 3 months ago
Learning Context for Collective Activity Recognition
In this paper we present a framework for the recognition of collective human activities. A collective activity is defined or reinforced by the existence of coherent behavior of i...
Wongun Choi, Silvio Savarese, Khuram Shahid
CVPR
2005
IEEE
14 years 9 months ago
Diagram Structure Recognition by Bayesian Conditional Random Fields
Hand-drawn diagrams present a complex recognition problem. Elements of the diagram are often individually ambiguous, and require context to be interpreted. We present a recognitio...
Yuan (Alan) Qi, Martin Szummer, Thomas P. Minka
AND
2010
13 years 5 months ago
Reshaping automatic speech transcripts for robust high-level spoken document analysis
High-level spoken document analysis is required in many applications seeking access to the semantic content of audio data, such as information retrieval, machine translation or au...
Julien Fayolle, Fabienne Moreau, Christian Raymond...
FLAIRS
2008
13 years 10 months ago
Learning Dynamic Naive Bayesian Classifiers
Hidden Markov models are a powerful technique to model and classify temporal sequences, such as in speech and gesture recognition. However, defining these models is still an art: ...
Miriam Martínez, Luis Enrique Sucar
TCSV
2008
102views more  TCSV 2008»
13 years 7 months ago
Semantic Analysis for Automatic Event Recognition and Segmentation of Wedding Ceremony Videos
Wedding is one of the most important ceremonies in our lives. It symbolizes the birth and creation of a new family. In this paper, we present a system for automatically segmenting ...
Wen-Huang Cheng, Yung-Yu Chuang, Yin-Tzu Lin, Chi-...