SVM-BASED PARAMETER SETTING OF SELF-QUOTIENT e-FILTER AND ITS APPLICATION TO NOISE ROBUST HUMAN DETECTION

Mitsuharu Matsumoto

2011

Abstract

This paper describes SVM-based parameter setting of self-quotient ɛ-filter (SQEF), and its application to noise robust human detection combining SQEF, histograms of oriented gradients (HOG), and support vector machine (SVM). Although human detection combining HOG and SVM is a powerful approach, as it uses local intensity gradients, it is difficult to handle noise corrupted images. On the other hand, although human detection combining SQEF, HOG and SVM can realize noise robust human detection, SQEF requires manual parameter setting. Our aim is not only to train SVM but also to adjust the parameter of self-quotient ɛ-filter using the trained SVM in training procedure. The experimental results show that we can realize noise robust human detection by using SQEF with the obtained parameter, HOG and SVM trained by intact images without noise.

References

  1. Arakawa, K. and Okada, T. (2005). e -separating nonlinear filter bank and its application to face image beautification. In IEICE Transactions on Fundamentals, pages 1216-1225. IEICE.
  2. Belongie, S., Malik, J., and Puzicha, J. (2001). Matching shapes. In Proc. of Int'l Conf. on Computer Vision, pages 454-461. IEEE.
  3. Chang, C.-C. and Lin, C.-J. (2001). LIBSVM: a library for support vector machines. In http://www.csie.ntu.edu.tw/ cjlin/libsvm.
  4. Dalal, N. and Triggs, B. (2005). Histograms of oriented gradients for human detection. In Proc. of Int'l Conf. on Computer Vision and Pattern Recognition., pages 886-893. IEEE.
  5. Freeman, W. T., Tanaka, K., Ohta, J., and Kyuma, K. (1996). Computer vision for computer games. In Proc. of Int'l Conf. on Automatic Face and Gesture Recognition, pages 100-105. IEEE.
  6. Gooch, B., Reinhard, E., and Gooch, A. (2004). Human facial illustrations: Creations and psychological evaluation. In ACM transactions on Graphics, pages 27-44. ACM.
  7. Himayat, N. and Kassam, S. (1993). Approximate performance analysis of edge preserving filters. In IEEE Trans. on Signal Processing., pages 2764-2777. IEEE.
  8. Lowe, D. G. (2004). Distinctive image features from scaleinvariant keypoints. In Int'l Journal of Computer Vision, volume 60, pages 91-110. Springer.
  9. Matsumoto, M. (2010a). Feature extraction from noisy face image using self-quotient e -filter. Proc. of Int'l Conf. on Computer Engineering and Technology, pages 395-399.
  10. Matsumoto, M. (2010b). Self-quotient e -filter for feature extraction from noise corrupted image. IEICE Trans. on Infomation and Systems.
  11. Papageorgiou, C. and Poggio, T. (2000). A trainable system for object detection. In Int'l Journal of Computer Vision, volume 38, pages 15-33. Springer.
  12. Tomasi, C. and Manduchi, R. (1998). Bilateral filtering for gray and color images. In Proc. of Int'l Conf. on Computer Vision. IEEE.
  13. Viola, P., Jones, M. J., and Snow, D. (2003). Detecting pedestrians using patterns of motion and appearance. In Proc. of Int'l Conf. on Computer Vision, volume 1, pages 734-741. IEEE.
  14. Wang, H., Li., S. Z., and Wang, Y. (2004). Face recognition under varying lighting conditions using self quotient image. In Proc. of Int'l Conf. on Automation Face and Gesture Recognition. IEEE.
Download


Paper Citation


in Harvard Style

Matsumoto M. (2011). SVM-BASED PARAMETER SETTING OF SELF-QUOTIENT e-FILTER AND ITS APPLICATION TO NOISE ROBUST HUMAN DETECTION . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 290-295. DOI: 10.5220/0003177102900295


in Bibtex Style

@conference{icaart11,
author={Mitsuharu Matsumoto},
title={SVM-BASED PARAMETER SETTING OF SELF-QUOTIENT e-FILTER AND ITS APPLICATION TO NOISE ROBUST HUMAN DETECTION},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={290-295},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003177102900295},
isbn={978-989-8425-40-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - SVM-BASED PARAMETER SETTING OF SELF-QUOTIENT e-FILTER AND ITS APPLICATION TO NOISE ROBUST HUMAN DETECTION
SN - 978-989-8425-40-9
AU - Matsumoto M.
PY - 2011
SP - 290
EP - 295
DO - 10.5220/0003177102900295