Efficient rectangle feature extraction for real-time facial expression recognition based on AdaBoost

In this paper, we propose a method of selecting new types of rectangle features that are suitable for facial expression recognition. The basic concept in this paper is similar to Violar's approach, which is used for face detection. Instead of previous Haar-like rectangle features, we choose rec...

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Bibliographic Details
Main Authors: Sung Uk Jung, Do Hyoung Kim, Kwang Ho An, Myung Jin Chung
Format: Conference Proceeding
Language:English
Subjects:
Active appearance model
AdaBoost
Computer science
Face detection
Face recognition
facial expression recognition
Feature extraction
feature selection
Humans
Pattern classification
Pattern recognition
Principal component analysis
rectangle feature
Solid modeling
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Description
Summary:In this paper, we propose a method of selecting new types of rectangle features that are suitable for facial expression recognition. The basic concept in this paper is similar to Violar's approach, which is used for face detection. Instead of previous Haar-like rectangle features, we choose rectangle features for facial expression recognition among all possible rectangle types in a 3/spl times/3 matrix form using the AdaBoost algorithm. Also, the facial expression recognition system constituted with the proposed rectangle features is compared to that with previous rectangle features with regard to its capacity. The results show that the proposed approach has better performance in facial expression recognition in terms of simulation and experimental results.
ISSN:2153-0858
2153-0866
DOI:10.1109/IROS.2005.1545534