Face Recognition Using Face-ARG Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A sensitivity analysis method and its application in physics-based nonrigid motion modeling
Image and Vision Computing
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Pattern Recognition
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Machine Vision and Applications
Using multi-instance enrollment to improve performance of 3D face recognition
Computer Vision and Image Understanding
Factors that influence algorithm performance in the Face Recognition Grand Challenge
Computer Vision and Image Understanding
A meta-analysis of face recognition covariates
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
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This paper investigates face recognition during facial expressions. While face-expressions have been treated as an adverse factor in standard face recognition approaches, our research suggests that if a system has a choice in the selection of faces to use in training and recognition, its best performance would be obtained on faces displaying expressions. Naturally, smiling faces are the most prevalent (among expressive faces) for both training and recognition in dynamic scenarios. We employ a measure of Discrimination Power that is computed from between-class and within-class scatter matrices. Two databases are used to show the performance differences on different sets of faces.