Age classification combining contour and texture feature

Authors:
Yan-Ming Tang;Bao-Liang Lu
Affiliations:
Center for Brain-Like Computing and Machine Intelligence, Department of Computer Science and Engineering, Shanghai, Jiao Tong University, Shanghai, China;Center for Brain-Like Computing and Machine Intelligence, Department of Computer Science and Eng., Shanghai, Jiao Tong Univ., Shanghai, China and MOE-Microsoft Key Lab. for Int. Computing and Int. ...
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Year:
2010

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Abstract

Age classification based on computer vision has widespread applications. Most of previous works only utilize texture feature or use contour and texture feature separately. In this paper, we proposed an age classification system that integrate contour and texture information. Besides, we improve the traditional Local Binary Pattern(LBP) feature extraction method and get pure texture feature. Support Vector Machines with probabilistic output (SVM-PO) is used as individual classifiers. Then we use combination mechanism based on fuzzy integral to merge the output of different classifiers. The experiment results show pure texture feature outperforms other features and it can be well combined with contour feature.