Active shape models—their training and application
Computer Vision and Image Understanding
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
λτ-Space Representation of Images and Generalized Edge Detector
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generalized Image Matching: Statistical Learning of Physically-Based Deformations
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Image Compression Based on Centipede Model
ICIAP '97 Proceedings of the 9th International Conference on Image Analysis and Processing-Volume I - Volume I
Facial Analysis and Synthesis Using Image-Based Models
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Subspace analysis and optimization for AAM based face alignment
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
A review of active appearance models
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Face model fitting with learned displacement experts and multi-band images
Pattern Recognition and Image Analysis
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In this study, we present a new multi-band image representation for improving AAM segmentation accuracy for illumination invariant face alignment. AAM is known to be very sensitive to the illumination variations. We have shown that edges, originating from object boundaries are far less susceptible to illumination changes. Here, we propose a contour selector which mostly collects contours originating from boundaries of the face components (eyes, nose, chin, etc.) and eliminates the others arising from texture. Rather than representing the image using grey values, we use Hill, Hue and Grey value (HHG) for image representation. We demonstrate that HHG representation gives more accurate and reliable results as compared to image intensity alone under various lighting conditions.