A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
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Iterative point matching for registration of free-form curves and surfaces
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Active shape models—their training and application
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Towards a General Multi-View Registration Technique
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COSMOS-A Representation Scheme for 3D Free-Form Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Volumetric Segmentation via 3D Active Shape Models
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
Active Appearance Models Revisited
International Journal of Computer Vision
A Fast Multi-Modal Approach to Facial Feature Detection
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
Detection of Anchor Points for 3D Face Veri.cation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A New Method for Automatic 3D Face Registration
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Automatic Feature Extraction for Multiview 3D Face Recognition
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
How effective are landmarks and their geometry for face recognition?
Computer Vision and Image Understanding
Fully Automatic Registration of 3D Point Clouds
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic 3D face verification from range data
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
3D face detection using curvature analysis
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition from 2D and 3D images using 3D Gabor filters
Image and Vision Computing
Real-time combined 2D+3D active appearance models
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A review of recent advances in 3D ear- and expression-invariant face biometrics
ACM Computing Surveys (CSUR)
3D human face description: landmarks measures and geometrical features
Image and Vision Computing
3D/4D facial expression analysis: An advanced annotated face model approach
Image and Vision Computing
A pose-independent method for 3D face landmark formalization
Computer Methods and Programs in Biomedicine
3D facial landmark localization using combinatorial search and shape regression
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Random Forests for Real Time 3D Face Analysis
International Journal of Computer Vision
3D human face soft tissues landmarking method: An advanced approach
Computers in Industry
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We present an accurate and robust framework for detecting and segmenting faces, localizing landmarks, and achieving fine registration of face meshes based on the fitting of a facial model. This model is based on a 3-D Point Distribution Model (PDM) that is fitted without relying on texture, pose, or orientation information. Fitting is initialized using candidate locations on the mesh, which are extracted from low-level curvature-based feature maps. Face detection is performed by classifying the transformations between model points and candidate vertices based on the upper-bound of the deviation of the parameters from the mean model. Landmark localization is performed on the segmented face by finding the transformation that minimizes the deviation of the model from the mean shape. Face registration is obtained using prior anthropometric knowledge and the localized landmarks. The performance of face detection is evaluated on a database of faces and non-face objects where we achieve an accuracy of 99.6%. We also demonstrate face detection and segmentation on objects with different scale and pose. The robustness of landmark localization is evaluated with noisy data and by varying the number of shapes and model points used in the model learning phase. Finally, face registration is compared with the traditional Iterative Closest Point (ICP) method and evaluated through a face retrieval and recognition framework on the GavabDB dataset, where we achieve a recognition rate of 87.4% and a retrieval rate of 83.9%.