Discrete-time signal processing
Discrete-time signal processing
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comprehensive Database for Facial Expression Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
An Investigation into the Use of Partial-Faces for Face Recognition
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Facial asymmetry quantification for expression invariant human identification
Computer Vision and Image Understanding - Special issue on Face recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Local facial asymmetry for expression classification
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Hi-index | 0.00 |
Facial asymmetry has now been established as a useful biometric for human identification in the presence of expression variations ([1]). The current paper investigates an alternative representation of asymmetry in the frequency domain framework, and its significance in identification tasks in terms of the phase component of the frequency spectrum of an image. The importance of the latter in face reconstruction is well-known in the engineering literature ([2]) and this establishes a firm ground for the success of asymmetry as a potentially useful biometric. We also point out some useful implications of this connection and dual representation. Moreover, the frequency domain features are shown to be more robust to intra-personal distortions than the corresponding spatial measures and yield error rates as low as 4% on a dataset with images showing extreme expression variations.