Abstract
Research on 3D face models relies on extraction of feature points for segmentation, registration, or recognition. Robust feature point extraction from pure geometric surface data is still a challenging issue. In this project, we attempt to automatically extract feature points from 3D range face models without texture information. Human facial surface is overall convex in shape and a majority of the feature points are contained in concave regions within this generally convex structure. These “feature-rich” regions occupy a relatively small portion of the entire face surface area. We propose a novel approach that looks for features only in regions with a high density of concave points and ignores all convex regions. We apply an iso-geodesic stripe approach to limit the search region, and apply the shape-index integral projection to locate the features of interest. Finally, eight individual features (i.e., inner corners of eye, outer corners of eye, nose sides, and outer lip corners) are detected on 3D range models. The algorithm is evaluated on publicly available 3D databases and achieved over 90% accuracy on average.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zhao, W., Chellappa, R., Phillips, P.J., Rosenfeld, A.: Face Recognition: A Literature Survey. ACM Computing Surveys 35(4), 399–458 (2003)
Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Chang, J., Hoffman, K., Marques, J., Min, J., Worek, W.: Overview of the Face Recognition Grand Challenge. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (2005)
Blanz, V., Vetter, T.: A morphable model for the synthesis of 3D faces. In: SIGGRAPH 1999, pp. 187–194 (1999)
Blanz, V., Scherbaum, K., Seidel, H.: Fitting a morphable model to 3D scans of faces. In: IEEE International Conference on Computer Vision, ICCV (2007)
Sun, Y., Chen, X., Rosato, M., Yin, L.: Tracking vertex flow and model adaptation for 3D spatio-temporal face analysis. IEEE Trans. on System, Man, and Cybernetics – Part A 40(3), 461–474 (2010)
Mpiperis, I., Malassiotis, S., Strintzis, M.: Bilinear Models for 3-D Face and Facial Expression Recognition. IEEE Trans. on Information Forensic and Security 3(3), 498–511 (2008)
Wang, S., Wang, Y., Gu, X., Samaras, D.: 3D surface matching and recognition using conformal geometry. In: IEEE International Conference on Computer Vision and Pattern Recognition, CVPR (2006)
Wang, Y., Gupta, M., Zhang, S., Wang, S., Gu, X., Samaras, D., Huang, P.: High resolution tracking of non-rigid motion of densely sampled 3D data using harmonic maps. International Journal of Computer Vision 76(3), 283–300 (2008)
Zeng, Y., Wang, C., Wang, Y., Gu, X., Samaras, D., Paragios, N.: Dense Non-rigid Surface Registration Using High-Order Graph Matching. In: IEEE International Conference on Computer Vision and Pattern recognition, CVPR (2010)
Berretti, S., Bimbo, A., Pala, P.: Description and retrieval of 3d face models using iso-geodesic stripes. In: Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval, MIR (2006)
Besl, P.: The Free-Form Surface Matching Problem. In: Freeman, H. (ed.) Machine Vision for Three-Dimensional Scenes, pp. 25–71. Academic Press, New York (1990)
Dorai, C., Jain, A.: Cosmosa representation scheme for 3d free-form objects. IEEE Trans. Pattern Analysis and Machine Intelligence 19(10) (1997)
Sun, Y., Yin, L.: Automatic Pose Estimation of 3D Models. In: IEEE/IAPR International Conference on Pattern Recognition, ICPR (2008)
Yin, L., Chen, X., Sun, Y., Worm, T., Reale, M.: A High-Resolution 3D Dynamic Facial Expression Database. In: The 8th International Conference on Automatic Face and Gesture Recognition (FG 2008), Amsterdam, the Netherlands (2008)
Milnor, J.: Morse Theory. Princeton University Press, Princeton (1963)
Yin, L., Wei, X., Sun, Y., Wang, J., Rosato, M.: A 3D Facial Expression Database For Facial Behavior Research. In: The 7th International Conference on Automatic Face and Gesture Recognition (FG 2006), Southampton, UK, pp. p211–p216, April 10-12 (2006)
Koenderink, J., van Doorn, A.: Surface shape and curvature scales. Image and Vision Computing 10(8), 557–564 (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Allen, J., Karkera, N., Yin, L. (2011). 3D Facial Feature Detection Using Iso-Geodesic Stripes and Shape-Index Based Integral Projection. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6939. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24031-7_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-24031-7_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24030-0
Online ISBN: 978-3-642-24031-7
eBook Packages: Computer ScienceComputer Science (R0)