Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30076
Fast Facial Feature Extraction and Matching with Artificial Face Models

Authors: Y. H. Tsai, Y. W. Chen

Abstract:

Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy.

Keywords: Facial feature extraction, AdaBoost, Active shapemodel, Hausdorff distance

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1061677

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1434

References:


[1] G. P. Campadelli and R. Lanzarotti, "Fiducial point localization in color images of face foregrounds," Image and Vision Computing, vol. 22, pp. 863-872, 2004.
[2] J. Matas, P. B'─▒lek, M. Hamouz, and J. Kittler, "Discriminative regions for human face detection," in in Proceedings of Asian Conference on Computer Vision, 2002.
[3] M. Hamouz, J. Kittler, J.-K. Kamarainen, P. Paalanen, H. Kalviainen, and J. Matas, "Feature-based affine-invariant localization of faces," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 9, pp. 1490-1495, 2005.
[4] T. Kim, H. Kim, W. Hwang, S. Kee, and J. Kittler, "Component-based LDA face descriptor for image retrieval," in The 13th British Machine Vision Conference, 2002.
[5] H. Jee, K. Lee, and S. Pan, "Eye and face detection using svm," in Intelligent Sensors, Sensor Networks and Information Processing Conference, pp. 577-580, 2004.
[6] Z. Zhu and Q. Ji, "Robust real-time eye detection and tracking under variable lighting conditions and various face orientations," Comput. Vis. Image Underst., vol. 98, no. 1, pp. 124-154, 2005.
[7] M. H. Nguyen, J. Perez, and F. D. la Torre Frade, "Facial feature detection with optimal pixel reduction svms," in 8th IEEE International Conference on Automatic Face and Gesture Recognition, September 2008.
[8] Y.-S. Ryu and S.-Y. Oh, "Automatic extraction of eye and mouth fields from a face image using eigenfeatures and ensemble networks," Applied Intelligence, vol. 17, no. 2, pp. 171-185, 2002.
[9] S. Duffner and C. Garcia, "A connexionist approach for robust and precise facial feature detection in complex scenes," in Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, pp. 316-321, Sept. 2005.
[10] P. Viola, M. J. Jonse, "Robust Real-Time Face Detection," International Journal of Computer Vision, vol. 57, no. 2, pp. 137-154, 2004.
[11] S. Milborrow and F. Nicolls, "Locating facial features with an extended active shape model," in ECCV 08, pp. IV: 504-513, 2008.
[12] Z.-L. Zheng and F. Yang, "Enhanced active shape model for facial feature localization," in 2008 International Conference on Machine Learning and Cybernetics, vol. 5, pp. 2841-2845, July 2008.
[13] M. Haj, J. Orozco, J. Gonzalez, and J. Villanueva, "Automatic face and facial features initialization for robust and accurate tracking," in International Conference on Pattern Recognition, pp. 1-4, 2008.
[14] Y. Freund and R. E. Schapire, "Experiments with a New Boosting Aalgorithm," in 13th International Conference on Machine Learning, pp. 148-156, 1996.
[15] R. E. Schapire and Y. Singer, "Improved Boosting Algorithms Using Confidence-rated Predictions." Machine Learning, vol. 37, no. 3, pp. 297-336, 1999.
[16] J. Friedman, T. Hastie, and R. Tibshirani, "Additive Logistic Regression: a Statistical View of Boosting," The Annals of Statistics, vol.28, no.2, pp.337-407, 2000.
[17] L. L. Huang, A. Shimizu, "A multi-expert approach for robust face detection," Pattern Recognition, vol. 39, pp. 1695-1703, 2006.
[18] R. L. Hsu, M. A. Mottaleb, A.K. Jain, Face detection in color images, IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, pp. 695- 705, 2002.
[19] A. Cheddad, J. Condell, K. Curran, P. Kevitt, "A skin tone detection algorithm for an adaptive approach to steganography," Singal Processing, vol.89, pp. 2465-2478, 2009.
[20] R.C. Gonzalez and R.E. Woods, Digital image processing, Addison-Wesley Publishing Company, Inc., 1992.
[21] D.P. Huttenlocher, G.A. Klanderman, W.J. Rucklidge, Comparing images using the Hausdorff distance, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 9, pp. 850-863, 1993.
[22] http://www.y28predictions.com/program/index.php