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Vol. 4 No. 1 (2013)
July-December

Articles

Face and gesture recognition by using a relevance analysis with 3D images

https://doi.org/10.19053/20278306.2563

Published 2013-08-15

  • Alexander Cerón Correa
    • ,
  • Augusto Enrique Salazar Jimenez
    • ,
  • Flavio Augusto Prieto Ortiz

Alexander Cerón Correa
Universidad Nacional de Colombia

Augusto Enrique Salazar Jimenez
Universidad Nacional de Colombia

Flavio Augusto Prieto Ortiz
Universidad Nacional de Colombia

Abstract

The 3D face recognition aims to reduce the flaws that present the bi-dimensional based methods. This kind of recognizing method has the advantage to be invariant to illumination changes because the faces are represented as a points cloud or a 3D mesh where the most remarkable is the geometry. In this research work we present a recognizing system that uses a set of 3D shape descriptors that were selected from a relevance analysis by using the Fisher coefficients in different regions of face which are part of an anthropometric face model. A set of experiments for face, expression, and gender recognition and were performed using the relevance analysis proposed. The obtained results show that the relevance analysis offers an increasing of the performance in face recognition system.

 

Keywords

3D face recognition, 3D segmentation, 3D shape descriptor, machine learning, relevance analysis.

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Author Biography

Alexander Cerón Correa

Ingeniero de Sistemas, MSc., Profesor Asociado, Facultad de Ingeniería, Universidad Militar Nueva Granada, Bogotá, Colombia. Estudiante de Doctorado en ingeniería de Sistemas y Computación. Universidad Nacional de Colombia

Augusto Enrique Salazar Jimenez

Ingeniero Electrónico, MSc. y candidato a PhD, Grupo de Automática y Electrónica, Instituto Tecnológico Metropolitano

Flavio Augusto Prieto Ortiz

Ingeniero Electrónico, PhD en ingenieria, Profesor Titular, Facultad de Ingeniería,

Universidad Nacional de Colombia - Sede Bogotá

References

  • Bishop, C. (2006). Pattern Recognition and Machine Learning. Springer Science Business + Media, LLC.
  • Cartoux J., Lapreste J., & Richetin, M. (1989). Face authentification or recognition by profile extraction from range images. Proceedings of the Workshop on Interpretation of 3D Scenes, 194–199.
  • Cerón, A., Salazar, A., & Prieto, F. (2010a). Análisis de relevancia de descriptores de forma 3D sobre la superficie del rostro. Memorias del Encuentro Nacional de Investigación y Desarrollo – Enid.
  • Cerón, A., Salazar, A., & Prieto, F. (2010b). Relevance analysis of 3d curvature-based shape descriptors on interest points of the face. Image Processing Theory Tools and Applications (IPTA), Proceedings of International Conference on Image Processing Theory, Tools and Applications. Pp. 452-457. DOI: 10.1109/IPTA.2010.5586721
  • Colbry, D., Stockman, G., & Jain, A. (2005). Detection of anchor points for 3D face verification. Proceedings of IEEE Workshop on Advanced 3D Imaging for Safety and Security.
  • Colombo, A., Cusano, C., & Schettini, R. (2006). 3D face detection using curvature analysis. Journal of Pattern Recognition, 39, 444–455.
  • Deo, D., & Sen, D. (2005). Automatic Recognition of Facial Features and Landmarking of Digital Human Head. In: 6th International Conference on Computer-Aided Industrial Design and Conceptual Design (CAID&CD), Delft, Netherlands.
  • Dinh, H., & Kropac, S. (2006). Multi-resolution spin-images. Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 06). vol.1, pp. 863 - 870
  • DOI: 10.1109/CVPR.2006.197
  • Dong, J., Krzyzak, A., & Suen, C. (2002). A practical SMO algorithm. Proceedings International Conference Pattern Recognition.
  • Duda, R., & Hart, P. (1998). Pattern Classification and Scene Analysis. Recuperado de http://www.gbv.de/dms/hebis-darmstadt/toc/32595522.pdf
  • Flynn, P.J., & Jain, A.K. (1988). Hypothesis testing and parameter estimation. Computer Society Conference on Computer Vision and Pattern Recognition, 261 – 267.
  • Gordon, G. (1991). Face recognition based on depth maps and surface curvature. Proceedings of SPIE Geometric methods in Computer Vision, 234–247.
  • Guangpeng, Z., & Yunhong, W. (2007). A 3D facial feature point localization method based on statistical shape model. Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP 2007, vol 2, 249 – 252.
  • Hallinan, P., Gordon, G., Yuille, L., Giblin, P., & Mumford, D. (1999). Two- and three-dimensional patterns of the face. A.K. Peters, Ltd.
  • Hearn, D. & Baker, P. (2003). Computer Graphics with OpenGL. Prentice Hall.
  • Ho, H., & Gibbins, D. (2008). Multi-scale feature extraction for 3D surface registration using local shape variation. Image and Vision Computing New Zealand, IVCNZ . 23rd International Conference.
  • DOI: 10.1109/IVCNZ.2008.4762120
  • Irfanoglu M., Gokberk B., & Akarun, L. (2004). 3D shape-based face recognition using automatically registered facial surfaces. Pattern Recognition. Proceedings of 17th International Conference on Pattern Recognition (ICPR 2004), vol 4, 183–186. DOI: 10.1109/ICPR.2004.1333734
  • Jagannathan, A., & Miller, E. (2007). Three-dimensional surface mesh segmentation using curvedness-based region growing approach. IEEE Transactions Pattern Analysis and Machine Intelligence, 29(12):2195–2204.
  • Johnson, A. (1997). Spin-Images: A Representation for 3-D Surface Matching. Carnegie Mellon University: PhD thesis. Recuperado de: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.71.4190&rep=rep1&type=pdf
  • Koenderink, J., & Van Doorn, A. (1992). Surface shape and curvature scales. Image and Vision Computing, 10, 557 – 56.
  • Leal, E., Branch, J., & Ortega, O. (2007). Estimación de curvaturas y direcciones principales en nube de puntos no organizados. Revista Dyna, 153, 351–362.
  • Lee, J.C., & Milios, E. (1990). Matching range images of human faces. Computer Vision, 1990. Proceedings, Third International Conference on computer vision 722-726.
  • DOI: 10.1109/ICCV.1990.139627
  • Lee, J. (2005). 3D face recognition using range images. Technical report, Department of Electrical and Computer Engineering, The University of Texas, Austin, TX. Recuperado de: http://users.ece.utexas.edu/~bevans/courses/ee381k/projects/spring05/lee/LitSurveyReport.pdf
  • Lu, X., Colbry, D., & Jain, A. (2004). Three-dimensional model based face recognition. Proceedings of 17th International Conference on Pattern Recognition, vol. 1, (pp 362–366).
  • Lu, X., Colbry, D., & Jain, A. (2006). Matching 2.5D scans to 3D models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(1), 31–43.
  • MeshLab. http://meshlab.sourceforge.net.
  • Moreno-Díaz. A.B. (2004). Reconocimiento Facial Automático mediante Técnicas de Visión Tridimensional. Universidad Politécnica de Madrid: Tesis Doctoral. Recuperado de: http://oa.upm.es/625/1/10200408.pdf
  • Salazar, A.E., & Prieto, F.A. (2010). 3D BSM for face segmentation and landmarks detection. Three-Dimensional Image Processing (3DIP) and Applications.
  • Sun, Y., & Yin, L. (2008). Automatic pose estimation of 3d facial models. En: Proceedings of 19th International Conference on Pattern Recognition. ICPR 2008, 1–4.
  • Tanaka, H., Ikeda, M., & Chiaki, H. (1998). Curvature-based face surface recognition using spherical correlation. Principal directions for curved object recognition. Automatic Face and Gesture Recognition, Proceding of Third IEEE International Conference on Automatic Face and Gesture Recognition. Proceedings, 372–377. DOI: 10.1109/AFGR.1998.670977
  • Taubin, G. (1995). Estimating the tensor of curvature of a surface from a polyhedral approximation. Fifth International Conference on Computer Vision (ICCV).
  • Xue, F., & Ding, X. (2006). 3D+2D face localization using boosting in multi-modal feature space. Proceedings of 18th International Conference on Pattern Recognition (ICPR’06).
  • Yin, L., Wei, X., Sun, Y., Wang, J., & Rosato, M. (2006). A 3D facialexpression database for facial behavior research. Automatic Face and Gesture Recognition, FGR 2006, In 7th International Conference on Automatic Face and Gesture Recognition (FGR06).pp. 211-216. DOI: 10.1109/FGR.2006.6

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