FACE RECOGNITION WITH HISTOGRAMS OF ORIENTED GRADIENTS

Oscar Déniz, Gloria Bueno, Jesus Salido, Fernando de la Torre

Abstract

Histograms of Oriented Gradients have been recently used as discriminating features for face recognition. In this work we improve on that work in a number of aspects. As a first contribution, it identifies the necessity of performing feature selection or transformation, especially if HOG features are extracted from overlapping cells. Second, the use of four different face databases allowed us to conclude that, if HOG features are extracted from facial landmarks, the error of landmark localization plays a crucial role in the absolute recognition rates achievable. This implies that the recognition rates can be lower for easier databases if landmark localization is not well adapted to them. This prompted us to extract the features from a regular grid covering the whole image. Overall, these considerations allow to obtain a significant recognition rate increase (up to 10% in some subsets) on the standard FERET database with respect to previous work.

References

  1. Albiol, A., Monzo, D., Martin, A., Sastre, J., and Albiol, A. (2008). Face recognition using HOG-EBGM. Pattern Recognition Letters, 29(10):1537-1543.
  2. Baranda, J., Jeanne, V., and Braspenning, R. (2008). Efficiency improvement of human body detection with histograms of oriented gradients. In ICDSC08, pages 1-9.
  3. Bertozzi, M., Broggi, A., Rose, M. D., Felisa, M., Rakotomamonjy, A., and Suard, F. (2007). A pedestrian detector using histograms of oriented gradients and a support vector machine classifier. In Proc. Intelligent Transportation Systems Conference, pages 143-148.
  4. Beveridge, J., Bolme, D., Draper, B., and Teixeira, M. (2005). The CSU face identification evaluation system: Its purpose, features, and structure. MVA, 16(2):128-138.
  5. Chellappa, R., Wilson, C., and Sirohey, S. (1995). Human and machine recognition of faces: A survey. Proceedings IEEE, 83(5):705-740.
  6. Chellappa, R. and Zhao, W., editors (2005). Face Processing: Advanced Modeling and Methods. Elsevier.
  7. Chuang, C., Huang, S., Fu, L., and Hsiao, P. (2008). Monocular multi-human detection using augmented histograms of oriented gradients. In ICPR08, pages 1-4.
  8. Dalal, N. and Triggs, B. (2005). Histograms of oriented gradients for human detection. volume 1, pages 886- 893.
  9. He, N., Cao, J., and Song, L. (2008). Scale space histogram of oriented gradients for human detection. In International Symposium on Information Science and Engieering, 2008. ISISE 7808, pages 167-170.
  10. Kobayashi, T., Hidaka, A., and Kurita, T. (2008). Selection of histograms of oriented gradients features for pedestrian detection. pages 598-607.
  11. Martinez, A. and R.Benavente (1998). database. Technical Report 24, CVC.
  12. Monzo, D., Albiol, A., Sastre, J., and Albiol, A. (2008). HOG-EBGM vs. Gabor-EBGM. In Proc. Internacional Conference on Image Processing, San Diego, USA.
  13. Nguyen, M. and De la Torre, F. (2008). Local minima free parameterized appearance models. In IEEE Conference on Computer Vision and Pattern Recognition.
  14. Perdersoli, M., Gonzalez, J., Chakraborty, B., and Villanueva, J. (2007a). Boosting histograms of oriented gradients for human detection. In Proc. 2nd Computer Vision: Advances in Research and Development (CVCRD), pages 1-6.
  15. Perdersoli, M., Gonzalez, J., Chakraborty, B., and Villanueva, J. (2007b). Enhancing real-time human detection based on histograms of oriented gradients. In In 5th International Conference on Computer Recognition Systems (CORES'2007).
  16. Phillips, P., Moon, H., Rizvi, S., and Rauss, P. (2000). The FERET evaluation methodology for face-recognition algorithms. PAMI, 22(10):1090-1104.
  17. Samal, A. and Iyengar, P. A. (1992). Automatic recognition and analysis of human faces and facial expressions: A survey. Pattern Recognition, 25(1).
  18. Sim, T., Baker, S., , and Bsat, M. (2001). The CMU pose, illumination, and expression (PIE) database of human faces. Technical Report CMU-RI-TR-01-02, Robotics Institute, Pittsburgh, PA.
  19. Suard, F., Rakotomamonjy, A., Bensrhair, A., and Broggi, A. (2006). Pedestrian detection using infrared images and histograms of oriented gradients. In Intelligent Vehicles Symposium, Tokyo, Japan, pages 206-212.
  20. Wang, C. and Lien, J. (2007). Adaboost learning for human detection based on histograms of oriented gradients. In ACCV07, pages I: 885-895.
  21. Watanabe, T., Ito, S., and Yokoi, K. (2009). Co-occurrence histograms of oriented gradients for pedestrian detection. In PSIVT09, pages 37-47.
  22. Wiskott, L., Fellous, J., Krüger, N., and von der Malsburg, C. (1997). Face recognition by elastic bunch graph matching. In Sommer, G., Daniilidis, K., and Pauli, J., editors, Proc. 7th Intern. Conf. on Computer Analysis of Images and Patterns, CAIP'97, Kiel, number 1296, pages 456-463, Heidelberg. Springer-Verlag.
  23. Yale face database (2009). Yale face database. Last accessed: April 2009.
  24. Zhao, W., Chellappa, R., Phillips, P. J., and Rosenfeld, A. (2003). Face recognition: A literature survey. ACM Comput. Surv., 35(4):399-458.
  25. Zhu, Q., Yeh, M.-C., Cheng, K.-T., and Avidan, S. (2006). Fast human detection using a cascade of histograms of oriented gradients. In Proc. Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, pages 1491-1498.
Download


Paper Citation


in Harvard Style

Déniz O., Bueno G., Salido J. and de la Torre F. (2010). FACE RECOGNITION WITH HISTOGRAMS OF ORIENTED GRADIENTS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010) ISBN 978-989-674-029-0, pages 339-344. DOI: 10.5220/0002820503390344


in Bibtex Style

@conference{visapp10,
author={Oscar Déniz and Gloria Bueno and Jesus Salido and Fernando de la Torre},
title={FACE RECOGNITION WITH HISTOGRAMS OF ORIENTED GRADIENTS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)},
year={2010},
pages={339-344},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002820503390344},
isbn={978-989-674-029-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2010)
TI - FACE RECOGNITION WITH HISTOGRAMS OF ORIENTED GRADIENTS
SN - 978-989-674-029-0
AU - Déniz O.
AU - Bueno G.
AU - Salido J.
AU - de la Torre F.
PY - 2010
SP - 339
EP - 344
DO - 10.5220/0002820503390344