JACIII Vol.17 No.3 pp. 392-403
doi: 10.20965/jaciii.2013.p0392


Real-Time Face Decorations of Enlarging Eyes and Whitening Skin in Video Based on Face Posture Estimation by Particle Filter

Norikazu Ikoma and Gefan Zhang

Faculty of Engineering, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata-ku, Kita-kyushu, Fukuoka 804-8550, Japan

December 2, 2012
February 24, 2013
May 20, 2013
face decoration, posture estimation, video, particle filter, real-time

Decorations of face such as enlarging eyes, whitening skin, rendering face slim, and so on are commercially successful in amusement arcades especially in Japan for still image and off-line processing. This paper proposes to decorate human face in video on-line and in real-time processing. Face posture estimation using particle filter plays a key role to decorate the face by precisely determining position of the eyes as well as determining regional position of face. Our proposed method conducts two decorations, enlarging eyes and whitening skin, based on the estimation result of face posture. Real-time implementation of the proposed method has been demonstrated for real scenes of indoor situation.

Cite this article as:
Norikazu Ikoma and Gefan Zhang, “Real-Time Face Decorations of Enlarging Eyes and Whitening Skin in Video Based on Face Posture Estimation by Particle Filter,” J. Adv. Comput. Intell. Intell. Inform., Vol.17, No.3, pp. 392-403, 2013.
Data files:
  1. [1] A. Doucet, N. de Freitas, and N. J. Gordon (Eds.), “Sequential Monte Carlo Methods in Practice,” New York, Springer, 2001.
  2. [2] G. Zhang, N. Ikoma, H. Kawano, and H.Maeda, “Decoration of Human Face in Video Image by Estimating Eye Positions with Particle Filter,” Proc. of Asia-Pacific Signal and Information Processing Association Annual Summit and Conf., Xi’an China, Oct. 18-21, PID:118, 2011.
  3. [3] N. Ikoma, Y. Chen, H. Kawano, and H. Maeda, “Real-time Estimation of Face Posture by Eyes detection and tracking with Particle Filter,” Proc. of 4th Int. Symposium on Computational Intelligence and Industrial Applications, pp. 11-16, 2010.
  4. [4] X. Chen, Q. Yang, H. Liao, W. Sun, and S. Yu, “Real-Time Face Pose Estimation in Video Sequence,” Proc. of 2nd Int. Workshop on Education Technology and Computer Science (ETCS), pp. 24-27, 2010.
  5. [5] S. Abe, M. Morimoto, and K. Fujii, “Estimating face direction from wideview surveillance camera,” Proc. of World Automation Congress (WAC) 2010, pp. 1-6, 2010.
  6. [6] M. Shafi, F. Iqbal, and I. Ali, “Face pose estimation using distance transform and normalized cross-correlation,” Proc. of 2011 IEEE Int. Conf. on Signal and Image Processing Applications (ICSIPA), pp. 186-191, 2011.
  7. [7] H. Jingu and M. Savvides, “Generic 3D face pose estimation using facial shapes,” Proc. of 2011 Int. Joint Conf. on Biometrics (IJCB), pp. 1-8, 2011.
  8. [8] Y. Kim and H. Li, “Face pose estimation based on EHMM and SVM,” Proc. of 2011 Int. Conf. on Computer Science and Service System (CSSS), pp. 408-411, 2011.
  9. [9] S.-U. Jung and M. S. Nixon, “On using gait biometrics to enhance face pose estimation,” Proc. of 4h IEEE Int. Conf. on Biometrics: Theory Applications and Systems (BTAS), pp. 1-6, 2010.
  10. [10] S. J. Canavan and L. Yin, “Dynamic face appearance modeling and sight direction estimation based on local region tracking and scalespace topo-represention,” Proc. of IEEE Int. Conf. on Multimedia and Expo (ICME 2009), pp. 1230-1233, 2009.
  11. [11] F. Dornaika and B. Raducanu, “Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach,” Proc. of 2009 Workshop on Applications of Computer Vision (WACV), pp. 1-6, 2009.
  12. [12] V. Pathangay, S. Das, and T. Greiner, “Symmetry-based face pose estimation from a single uncalibrated view,” Proc. of 8th IEEE Int. Conf. on Automatic Face & Gesture Recognition, pp. 1-8, 2008.
  13. [13] R. Niese, A. Al-Hamadi, and B. Michaelis, “A Stereo and Colorbased Method for Face Pose Estimation and Facial Feature Extraction,” Proc. of 18th Int. Conf. on Pattern Recognition (ICPR 2006), pp. 299-302, 2006.
  14. [14] D. Takahashi and N. Okamoto, “Robust Posture Estimation of the Human Face in Rapid Lighting Changes using a 3-D Reference Picture,” Proc. of ’06 Canadian Conf. on Electrical and Computer Engineering, pp. 2078-2081, 2006.
  15. [15] D. Takahashi and N. Okamoto, “Robust posture estimation of human face in some bad conditions,” Proc. of Canadian Conf. on Electrical and Computer Engineering, pp. 1336-1339, 2005.
  16. [16] D. Takahashi and N. Okamoto, “Semi real-time algorithm for posture estimation of the human face using a 3-D reference picture,” Proc. of Canadian Conf. on Electrical and Computer Engineering, pp. 927-930, 2004.
  17. [17] Z. Yang, H. Ai, B. Wu, S. Lao, and L Cai, “Face pose estimation and its application in video shot selection,” Proc. of the 17th Int. Conf. on Pattern Recognition (ICPR2004), pp. 322-325, 2004.
  18. [18] P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” Proc. of 2001 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR 2001), pp. I-511-I-518, 2001.

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