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

  title={Efficient rectangle feature extraction for real-time facial expression recognition based on AdaBoost},
  author={Sung-Uk Jung and Do Hyoung Kim and Kwang Ho An and Myung Jin Chung},
  journal={2005 IEEE/RSJ International Conference on Intelligent Robots and Systems},
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… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 15 references

Classifying Facial Actions

IEEE Trans. Pattern Anal. Mach. Intell. • 1999
View 3 Excerpts
Highly Influenced

Real time facial expression recognition with AdaBoost

Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. • 2004

Comparing TemplateBased , FeatureBased and Supervised Classification of Facial Expressions form Static Images

W. A. Fellenz, S. Kollias

Comparision between GeometryBased and GaborWaveletsBased Facial Expression Recognition using Multi - Layer Perceptron

S. Akamatsu
Journal of Visual Communication and Image Representation • 1998

Face Image Analysis by Unsupervised Learning and Redundancy Reduction

M. S. Bartlett

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