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ICMCS
2005
IEEE

Facial Expression Recognition with Relevance Vector Machines

10 years 8 months ago
Facial Expression Recognition with Relevance Vector Machines
For many decades automatic facial expression recognition has scientifically been considered a real challenging problem in the fields of pattern recognition or robotic vision. The current research aims at proposing Relevance Vector Machines (RVM) as a novel classification technique for the recognition of facial expressions in static images. The aspects related to the use of Support Vector Machines are also presented. The data for testing were selected from the Cohn-Kanade Facial Expression Database. We report 90.84% recognition rates for RVM for six universal expressions based on a range of experiments. Some discussions on the comparison of different classification methods are included.
Dragos Datcu, Léon J. M. Rothkrantz
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICMCS
Authors Dragos Datcu, Léon J. M. Rothkrantz
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