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2006
IEEE

Learning to Identify Facial Expression During Detection Using Markov Decision Process

10 years 6 months ago
Learning to Identify Facial Expression During Detection Using Markov Decision Process
While there has been a great deal of research in face detection and recognition, there has been very limited work on identifying the expression on a face. Many current face detection methods use a Viola–Jones style “cascade” of Adaboost-based classifiers to detect faces. We demonstrate that faces with similar expression form “clusters” in a “classifier space” defined by the real-valued outcomes of these classifiers on the images and address the the task of using these classifiers to classify a new image into the appropriate cluster (expression). We formulate this as a Markov Decision Process and use dynamic programming to find an optimal policy — here a decision tree whose internal nodes each correspond to some classifier, whose arcs correspond to ranges of classifier values, and whose leaf nodes each correspond to a specific facial expression, augmented with a sequence of additional classifiers. We present empirical results that demonstrate that our system a...
Ramana Isukapalli, Ahmed M. Elgammal, Russell Grei
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where FGR
Authors Ramana Isukapalli, Ahmed M. Elgammal, Russell Greiner
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