Active shape models—their training and application
Computer Vision and Image Understanding
Detecting Faces in Images: A Survey
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
Facial features localization in front view head and shoulders images
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Locating Facial Features with an Extended Active Shape Model
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part IV
Head Pose Estimation in Computer Vision: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Appearance manifold of facial expression
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
IEEE Transactions on Image Processing
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This paper explores robust facial expression recognition techniques based on the underlying low dimensional manifolds embedded in facial images of varying expression. Faces are automatically detected and facial features are extracted, normalized and mapped onto a low dimensional projection surface using Locality Preserving Projections. Alternatively, processed image pixels are used for manifold construction. Classification models robustly estimate expression from the low dimensional projections in manifold space. This method performs robustly in natural settings, enabling more engaging human computer interfaces.