Surface shape and curvature scales
Image and Vision Computing
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Improving the Detection Performance in Semi-automatic Landmark Extraction
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Localization of 3D Anatomical Point Landmarks in 3D Tomographic Images Using Deformable Models
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Modern Differential Geometry of Curves and Surfaces with Mathematica, Third Edition (Studies in Advanced Mathematics)
Pose-space animation and transfer of facial details
Proceedings of the 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Landmark Localisation in 3D Face Data
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
From geometric to semantic human body models
Computers and Graphics
Point-pair descriptors for 3D facial landmark localisation
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
3D facial expression recognition using SIFT descriptors of automatically detected keypoints
The Visual Computer: International Journal of Computer Graphics - Special Issue on 3DOR 2010
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The face is perhaps the most important human anatomical part, and its study is very important in many fields, such as the medical one and the identification one. Technical literature presents many works on this topic involving bi-dimensional solutions. Even if these solutions are able to provide interesting results, they are strongly subjected to images distortion. Thanks to the significant improvements obtained in the 3D scanner domain (photogrammetry for instance), today it is possible to replace the 2D images with more precise and complete 3D models (triangulated points clouds). Working on three-dimensional data, in fact, it is possible to obtain a more complete set of information about the face morphology. At present, even if it is possible to find interesting papers on this field, there is the lack of a complete protocol for converting the big amount of data coming from the three-dimensional point clouds in a reliable set of facial data, which could be employed for recognition and medical tasks. Starting from some anatomical human face concepts, it has been possible to understand that some soft-tissue landmarks could be the right data set for supporting many processes working on three-dimensional models. So, working in the Differential Geometry domain, through the Coefficients of the Fundamental Forms, the Principal Curvatures, Mean and Gaussian Curvatures and also with the derivatives and the Shape and Curvedness Indexes, the study has proposed a structured methodology for soft-tissue landmark formalization in order to provide a methodology for their automatic identification. The proposed methodology and its sensitivity have been tested with the involvement of a series of subjects acquired in different scenarios.