Face Image Quality Assessment Based on Learning to Rank

Face image quality is an important factor affecting the accuracy of automatic face recognition. It is usually possible for practical recognition systems to capture multiple face images from each subject. Selecting face images with high quality for recognition is a promising stratagem for improving t...

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Bibliographic Details
Published inIEEE signal processing letters Vol. 22; no. 1; pp. 90 - 94
Main Authors Chen, Jiansheng, Deng, Yu, Bai, Gaocheng, Su, Guangda
Format Journal Article
LanguageEnglish
Published New York IEEE 01.01.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Assessments
Equations
Face
Face quality
Face recognition
Image quality
Image recognition
Learning
learning to rank
Object recognition
Quality assessment
Recognition
Robustness
Signal processing
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Summary:Face image quality is an important factor affecting the accuracy of automatic face recognition. It is usually possible for practical recognition systems to capture multiple face images from each subject. Selecting face images with high quality for recognition is a promising stratagem for improving the system performance. We propose a learning to rank based framework for assessing the face image quality. The proposed method is simple and can adapt to different recognition methods. Experimental result demonstrates its effectiveness in improving the robustness of face detection and recognition.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2014.2347419