Abstract
This paper proposes a solution algorithm to locate the facial features on the human face images. First, the proposed algorithm determines the face region based on skin-tone segmentation and morphological operations. Then, we locate the facial features (i.e. brows, eyes, and mouth) by their color information. Finally, this algorithm set the shape control points based on the Facial Animation Parameters in the MPEG-4 standard on the located facial features. Results of experiments to the face images show that the proposed approach is not only robust but also quit efficient.
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
Ahn, S., Ozawa, S.: Generating Facial Expressions Based on Estimation of Muscular Contraction Parameters From Facial Feature Points. In: IEEE International Conf. on Systems, Man, and Cybernetics, The Hague, Netherlands, October 10-13, vol. 1, pp. 660–665 (2004)
Zhang, Q., Liu, Z., Guo, B., Terzopoulos, D., Shum, H.Y.: Geometry-Driven Photorealistic Facial Expression Synthesis. IEEE Transactions on Visualization and Computer Graphics 12(1), 48–60 (2006)
Song, M., Tao, D., Liu, Z., Li, X., Zhou, M.: Image Ratio Features for Facial Expression Recognition Application. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 40(3), 779–788 (2010)
Pentland, A., Moghaddam, B., Starner, T.: View-based and modular eigenspaces for face recognition. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR 1994), Seattle, WA (1994)
Min Huang, W., Mariani, R.: Face detection and precise eyes location. In: Proc. Int. Conf. on Pattern Recognition, ICPR 2000 (2000)
Huang, J., Wechsler, H.: Eye detection using optimal wavelet packets and radial basis functions (rbfs). Int. J. Pattern Recognit. Artif. Intell. 13(7), 1009–1025 (1999)
Chellappa, R., Wilson, C.L., Sirohey, S.: Human and Machine Recognition of Faces: A Survey. Proc. IEEE. 83, 705–740 (1995)
Lam, K.L., Yan, H.: Locating and Extracting the Eye in Human Face Images. Pattern Recognition 29(5), 771–779 (1996)
Smeraldi, F., Carmona, O., Bigun, J.: Saccadic Search with Gabor Features Applied to Eye Detection and Real-time Head Tracking. Image and Vision Computing 18(4), 323–329 (2000)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)
Weber, M.: Unsupervised learning of models for object recognition. Ph.D. dissertation, California Inst. Technol., Pasadena (2000)
Fergus, R., Perona, P., Zisserman, A.: Object class recognition by unsupervised scale-invariant learning. In: Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition, pp. 264–271 (2003)
Kadir, T.: Scale, saliency and scene description. Ph.D. dissertation. Oxford Univ., Oxford, U.K (2002)
Phung, S.L., Bouzerdoum, A., Chai, D.: Skin Segmentation Using Color Pixel Classification: Analysis and Comparison. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(1), 148–154 (2005)
Tao, L., Wang, H.B.: Detecting and Locating Human Eyes in Face Images Based on Progressive Thresholding. In: Proc. of the 2007 IEEE International Conf. on Robotics and Biomimetics, Sanya, China, December 15-18, pp. 445–449 (2007)
Berbar, M.A., Kelash, H.M., Kandeel, A.A.: Faces and Facial Features Detection in Color Images. In: Proc. of the Geometric Modeling and Imaging –New Trends, July 05-06, pp. 209–214 (2006)
Guan, Y.: Robust Eye Detection from Facial Image based on Multi-cue Facial Information. In: Proc. of the 2007 IEEE International Conf. on Control and Automation, Guangzhou, China, May 30- June 1, pp. 1775–1778 (2007)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, New Jersey (2002)
ISO/IEC Standard 14496-2, Coding of Audio-Visual Objects: Visual (October 1998)
Song, M., Tao, D., Liu, Z., Li, X., Zhou, M.: Image Ratio Features for Facial Expression Recognition Application. IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 40(3), 779–788 (2010)
Ding, L., Martinez, A.M.: Features versus Context: An Approach for Precise and Detailed Detection and Delineation of Faces and Facial Features. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(11), 2022–2038 (2010)
Vezhnevets, V., Sazonov, V., Andreeva, A.: A Survey on Pixel-Based Skin Color Detection Techniques. In: Proc. of Graphicon 2003, Moscow, Russia, pp. 85–92 (September 2003)
Georgia Tech Face Database, http://www.anefian.com/face_reco.htm
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, HW., Wu, YM., Lu, YL., Hsiao, YT. (2012). Detection of Facial Features on Color Face Images. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28487-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-28487-8_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28486-1
Online ISBN: 978-3-642-28487-8
eBook Packages: Computer ScienceComputer Science (R0)