Person-Similarity Weighted Feature for Expression Recognition
Authors: 
Huachun Tan, Yu-Jin ZhangAuthors Info & Claims
Pages 712 - 721
Abstract
In this paper, a new method to extract person-independent expression feature based on HOSVD (Higher-Order Singular Value Decomposition) is proposed for facial expression recognition. With the assumption that similar persons have similar facial expression appearance and shape, person-similarity weighted expression feature is used to estimate the expression feature of the test person. As a result, the estimated expression feature can reduce the influence of individual caused by insufficient training data and becomes less person-dependent, and can be more robust to new persons. The proposed method has been tested on Cohn-Kanade facial expression database and Japanese Female Facial Expression (JAFFE) database. Person-independent experimental results show the efficiency of the proposed method.
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- Person-Similarity Weighted Feature for Expression Recognition
Index terms have been assigned to the content through auto-classification.
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Information
Published In
Nov 2007
585 pages
ISBN:978-3-540-76389-5
DOI:10.1007/978-3-540-76390-1
- Editors:
- Yasushi Yagi,
- Sing Bing Kang,
- In So Kweon,
- Hongbin Zha
© Springer-Verlag Berlin Heidelberg 2007.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 15 March 2023
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