Efficient and Effective Gabor Feature Representation for Face Detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32771
Efficient and Effective Gabor Feature Representation for Face Detection

Authors: Yasuomi D. Sato, Yasutaka Kuriya

Abstract:

We here propose improved version of elastic graph matching (EGM) as a face detector, called the multi-scale EGM (MS-EGM). In this improvement, Gabor wavelet-based pyramid reduces computational complexity for the feature representation often used in the conventional EGM, but preserving a critical amount of information about an image. The MS-EGM gives us higher detection performance than Viola-Jones object detection algorithm of the AdaBoost Haar-like feature cascade. We also show rapid detection speeds of the MS-EGM, comparable to the Viola-Jones method. We find fruitful benefits in the MS-EGM, in terms of topological feature representation for a face.

Keywords: Face detection, Gabor wavelet based pyramid, elastic graph matching, topological preservation, redundancy of computational complexity.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1073423

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1815

References:


[1] E. Hjelmas, B. K. Low, "Face Detection: A Survey." Computer Vision and Image Understanding, 83(3), pp. 236-274, 2001.
[2] N. Degtyarev, O. Seredin, "Comparative Testing of Face Detection Algorithms." In A. E lmoataz et al. (Eds.): ICISP 2010, LNCS 6134, pp. 200-209 , (Springer-Verlag, Heidelberg, 2010).
[3] P. Viola, M. J. Jones, "Rapid Object Detection using a Boosted Cascade of Simple." Proc. IEEE CVPR 2001, 2001.
[4] P. Viola, M. J. Jones, "Robust Real-Time Face Detection." International Journal of Computer Vision, 57(2), pp.137-154, 2004.
[5] M. Lades, J. C. Vorbrueggen, J. Buhmann, et al., "Distortion invariant object recognition in the dynamic link architecture." IEEE Transactions on Computers, vol.42, no. 3, pp. 300-311, 1993.
[6] L. Wiskott, J.-M. Fellous, N. Kruger, C. von der Malsburg, "Face Recognition by Elastic Bunch Graph Matching." IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7), pp. 775-779, 1997.
[7] C. von der Malsburg, "The correlation theory of brain function." Internal Report Max-Planck-Institute fur Biophysikalische Chemie, Postfach 2841, D-3400 Gottingen, FRG, 1981.
[8] P. Wolfrum, C. Wolff, J. Lucke, C. von der Malsburg, "A Recurrent Dynamic Model for Correspondence-Based Face Recognition." Journal of Vision, vol.8, pp.1-18, 2008.
[9] Y. D. Sato, J. Jitsev, J. Bornschein, D. Pamplona, C. Keck, C. von der Malsburg, "A Gabor Wavelet Pyramid-Based Object Detection Algorithm." In Proc. ISNN (2) pp.232-240, 2011.
[10] O. Jesorsky, K. Kirchberg, R. Frischholz, "Robust Face Detection Using the Hausdorff Distance." In J. Bigun and F. Smeraldi, editors, Audio and Video based Person Authentication - AVBPA 2001, Springer, pp.90-95, 2001.
[11] R. Lienhart, J. Maydt, "An extended set of Haar-like features for rapid object detection." Proc. Intern. Conf. on Image Processing 2002, pp.900- 903, 2002.
[12] A. Eleyan, H. Ozkaramanli, H. Demirel, "Complex wavelet transform- Based face recognition." EURASIPJournal on Advances in Signal Processing, vol. 2008, Article ID 185281, 13 pages, 2008.
[13] D. G. Lowe, "Object Recognition from Local Scale-Invariant Features." Proceedings of the International Conference on Computer Vision 1999, 2, pp.150-1157, 1999.
[14] D. G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints." International Journal of Computer Vision, 60(2) pp. 91-110, 2004.