Abstract
3D face was recently investigated for various applications, including biometrics and diagnosis. Describing facial surface, i.e. how it bends and which kinds of patches is composed by, is the aim of studies in Face Analysis, whose ultimate goal is to identify which features could be extracted from three-dimensional faces depending on the application. In this study, we propose 54 novel geometrical descriptors for Face Analysis. They are generated by composing primary geometrical descriptors such as mean, Gaussian, principal curvatures, shape index, curvedness, and the coefficients of the fundamental forms. The new descriptors were mapped on 217 facial depth maps and analysed in terms of descriptiveness of facial shape and exploitability for localizing landmark points. Automatic landmark extraction stands as the final aim of this analysis. Results showed that the newly generated descriptors are suitable to 3D face description and to support landmark localization procedures.
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References
Vezzetti, E.; F., M. Geometrical Descriptors For Human Face Morphological Analysis And Recognition. Robotics And Autonomous Systems, V. 60, N. 6, P. 928-939, 2012.
Moos, S. Et Al. Cleft Lip Pathology Diagnosis And Foetal Landmark Extraction Via 3d Geometrical Analysis. International Journal On Interactive Design And Manufacturing, P. 1-18, 2014.
Vezzetti, E.; F., M. 3d Human Face Description: Landmarks Measures And Geometrical Features. Image And Vision Computing, V. 30, N. 10, P. 698-712, 2012.
Vezzetti, E.; F., M. Geometry-Based 3d Face Morphology Analysis: Soft-Tissue Landmark Formalization. Multimedia Tools And Applications, P. 1-35, 2012.
Vezzetti, E.; Marcolin, F. 3d Landmarking In Multiexpression Face Analysis: A Preliminary Study On Eyebrows And Mouth. Aesthetic Plastic Surgery, V. 38, P. 796–811, 2014.
Vezzetti, E.; Calignano, F.; Moos, S. Computer-Aided Morphological Analysis For Maxillo-Facial Diagnostic: A Preliminary Study. Journal Of Plastic, Reconstructive & Aesthetic Surgery, V. 63, N. 2, P. 218-226, 2010.
Vezzetti, E.; Marcolin, F.; Fracastoro, G. 3d Face Recognition: An Automatic Strategy Based On Geometrical Descriptors And Landmarks. Robotics And Autonomous Systems, V. 62, N. 12, P. 1768-1776, 2014.
Vezzetti, E.; Marcolin, F.; Stola, V. 3d Human Face Soft Tissues Landmarking Method: An Advanced Approach. Computers In Industry, V. 64, N. 9, P. 1326–1354, 2013.
Vezzetti, E.; Moos, S.; Marcolin, F. Three-Dimensional Human Face Analysis: Soft Tissue Morphometry. Proceedings Of The Intersymp 2011. Baden-Baden, Germany: [S.N.]. 2011.
Vezzetti, E. Et Al. A Pose-Independent Method For 3d Face Landmark Formalization. Computer Methods And Programs In Biomedicine, V. 198, N. 3, P. 1078-1096, 2012.
Vezzetti, E. Et Al. Exploiting 3d Ultrasound For Fetal Diagnosis Purpose Through Facial Landmarking. Image Analysis & Stereology, V. 33, N. 3, P. 167-188, 2014.
Creusot, C.; Pears, N.; Austin, J. Automatic Keypoint Detection On 3d Faces Using A Dictionary Of Local Shapes. International Conference On 3d Imaging, Modeling, Processing, Visualization And Transmission (3dimpvt), P. 204-211, May 2011.
Creusot, C.; Pears, N.; Austin, J. 3d Landmark Model Discovery From A Registered Set Of Organic Shapes. Ieee Computesociety Conference On Computer Vision And Pattern Recognition Workshops (Cvprw), P. 57-64, June 2012.
Li, H.; Morvan, J. M.; Chen, L. 3d Facial Expression Recognition Based On Histograms Of Surface Differential Quantities. Advanced Concepts For Intelligent Vision Systems, P. 483-494, January 2011.
Yang, X. Et Al. Automatic 3d Facial Expression Recognition Using Geometric Scattering Representation. 11th Ieee International Conference And Workshops On Automatic Face And Gesture Recognition (Fg), V. 1, P. 1-6, May 2015.
Zhen, Q. Et Al. Muscular Movement Model Based Automatic 3d Facial Expression Recognition. Multimedia Modeling, P. 522-533, January 2015.
Li, H. Et Al. An Efficient Multimodal 2d+ 3d Feature-Based Approach To Automatic Facial Expression Recognition. Computer Vision And Image Understanding, V. 140, P. 83-92, 2015.
Li, Y. Et Al. 3d Facial Mesh Detection Using Geometric Saliency Of Surface. Ieee International Conference On Multimedia And Expo (Icme), P. 1-4, July 2011.
Zhang, G.; Wang, Y. Robust 3d Face Recognition Based On Resolution Invariant Features. Pattern Recognition Letters, V. 32, N. 7, P. 1009-1019, 2011.
Bagchi, P. Et Al. A Novel Approach To Nose-Tip And Eye Corners Detection Using Hk Curvature Analysis In Case Of 3d Images. Third International Conference On Emerging Applications Of Information Technology (Eait), P. 311-315, November 2012.
Szeptycki, P.; Ardabilian, M.; Chen, L. Nose Tip Localization On 2.5 D Facial Models Using Differential Geometry Based Point Signatures And Svm Classifier. Biosig-Proceedings Of The International Conference Of The Biometrics Special Interest Group, P. 1-12, September 2012.
Lanz, C. Et Al. Automated Classification Of Therapeutic Face Exercises Using The Kinect. Visapp, P. 556-565, 2013.
Rabiu, H. Et Al. 3d-Based Face Segmentation Using Adaptive Radius. Ieee International Conference On Signal And Image Processing Applications (Icsipa), P. 237-240, October 2013.
Zeng, W. Et Al. An Automatic 3d Expression Recognition Framework Based On Sparse Representation Of Conformal Images. 10th Ieee International Conference And Workshops On Automatic Face And Gesture Recognition, P. 1-8, April 2013.
Abbas, H.; Hicks, Y.; Marshall, D. Automatic Classification Of Facial Morphology For Medical Applications. Procedia Computer Science, P. 1649-1658, 2015.
Canavan, S. Et Al. Landmark Localization On 3d/4d Range Data Using A Shape Index-Based Statistical Shape Model With Global And Local Constraints. Computer Vision And Image Understanding, V. 139, P. 136-148, 2015.
Di Martino, J. M.; Fernandez, A.; Ferrari, J. 3d Curvature Analysis With A Novel One-Shot Technique. Ieee International Conference On Image Processing, P. 3818-3822, October 2014.
Perakis, P.; Theoharis, T.; Kakadiaris, I. A. Feature Fusion For Facial Landmark Detection. Pattern Recognition, V. 47, N. 9, P. 2783-2793, 2014.
Vezzetti, E. Adaptive Sampling Plan Design Methodology For Reverse Engineering Acquisition. The International Journal Of Advanced Manufacturing Technology, V. 42, N. 7-8, P. 780-792, 2009.
Vezzetti, E. Computer Aided Inspection: Design Of Customer-Oriented Benchmark For Noncontact 3d Scanner Evaluation. The International Journal Of Advanced Manufacturing Technology, V. 41, N. 11-12, P. 1140-1151, 2009.
Galantucci, L. M.; Percoco, G.; Di Gioia, E. Low Cost 3d Face Scanning Based On Landmarks And Photogrammetry. Intelligent Automation And Computer Engineering, P. 93-106, 2009.
Sforza, C.; Ferrario, V. F. Soft-Tissue Facial Anthropometry In Three Dimensions: From Anatomical Landmarks To Digital Morphology In Research, Clinics And Forensic Anthropology. Journal Of Anthopological Sciences, V. 84, P. 97-124, 2006.
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MARCOLIN, F. et al. (2017). Three-dimensional face analysis via new geometrical descriptors. In: Eynard, B., Nigrelli, V., Oliveri, S., Peris-Fajarnes, G., Rizzuti, S. (eds) Advances on Mechanics, Design Engineering and Manufacturing . Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-45781-9_75
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DOI: https://doi.org/10.1007/978-3-319-45781-9_75
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