孙怡
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Head-and-shoulder detection in varying pose
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Indexed by:会议论文

Date of Publication:2005-08-27

Included Journals:EI

Volume:3611

Issue:PART II

Page Number:12-20

Abstract:Head-and-shoulder detection has been an important research topic in the fields of image processing and computer vision. In this paper, a head-and-shoulder detection algorithm based on wavelet decomposition technique and support vector machine (SVM) is proposed. Wavelet decomposition is used to extract features from real images, and linear SVM and non-linear SVM are trained for detection. Non-head-and-shoulder images can be removed by the linear SVM firstly, and then non-linear SVM detects head-and-shoulder images in detail. Varying head-and-shoulder pose can be detected from frontal and side views, especially from rear view. The experiment results prove that the method proposed is effective and fast to some extent. © Springer-Verlag Berlin Heidelberg 2005.

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Gender:Female

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:信息与通信工程学院

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