Advertisement

Feature Fusion of HOG and GSP for Smile Recognition

  • Hemant Kumar MeenaEmail author
  • Kamlesh Kumar Sharma
  • S. D. Joshi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10325)

Abstract

Recognizing smile conveys the information about the happy mood and the acceptability of the message. The Histogram of Oriented Gradient (HOG) has been used to find out the face detection and the facial expression recognition. However, due to the large feature length of facial expression, there is a challenge to decrease the size of the feature vector. This paper demonstrates the proposed method for smile recognition on JAFFE dataset and Cohn-Kanade dataset by combining the HOG with Graph Signal Processing (GSP). Not only, the feature length is significantly reduced but also, the accuracy has been increased in the smile recognition using the proposed method.

References

  1. 1.
    Mehrabian, A.: Communication without words. Psychol. Today 2, 53–55 (1968)Google Scholar
  2. 2.
    Mandal, M.K., Pandey, R., Prasad, A.B.: Facial expressions of emotions and schizophrenia: a review. Schizophr. Bull. 24(3), 399–412 (1998)CrossRefGoogle Scholar
  3. 3.
    Lyons, M.J., Budynek, J., Akamatsu, S.: Automatic classification of single facial images. IEEE Trans. Pattern Anal. Mach. Intell. 21(12), 1357–1362 (1999)CrossRefGoogle Scholar
  4. 4.
    Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 1991), pp. 586–591 (1991)Google Scholar
  5. 5.
    Li, Y.: Smile recognition based on face texture and mouth shape features. In: IEEE Workshop on Electronics, Computer and Applications, pp. 606–609 (2014)Google Scholar
  6. 6.
    Bai, Y., Guo, L., Jin, L., Huang, Q.: A novel feature extraction method using pyramid histogram of orientation gradients for smile recognition. In: 16th IEEE International Conference on Image Processing (ICIP), pp. 3305–3308 (2009)Google Scholar
  7. 7.
    Fridlund, A.I.: Human facial expression: An evolutionary view. Academic Press, San Diego (1994)Google Scholar
  8. 8.
    Dalal, N., Triggs, B.: Histograms of oriented gradients for human Detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), vol. I, pp. 886–893 (2005)Google Scholar
  9. 9.
    Shuman, D.I., Narang, S.K., Frossard, P., Ortega, A., Vandergheynst, P.: The emerging field of signal processing on graphs: extending high-dimensional data analysis to networks and other irregular domains. IEEE Signal Process. Mag. 30(3), 83–98 (2013)CrossRefGoogle Scholar
  10. 10.
    Lyons, M.J., Akemastu, S., Kamachi, M., Gyoba,J.: Coding facial expressions with gabor wavelets. In: 3rd IEEE International Conference on Automatic Face and Gesture Recognition, pp. 200–205 (1998)Google Scholar
  11. 11.
    Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol. 1, pp. I-511–I-518 (2001)Google Scholar
  12. 12.
    He, X., Niyogi, P.: Locality preserving projections. In: NIPS, vol. 16 (2003)Google Scholar
  13. 13.
    Hong, L., Gao, Y., Wu, P.: Smile detection in unconstrained scenarios using self-similarity of gradients features. In: 2014 IEEE International Conference on Image Processing (ICIP), pp. 1455–1459 (2014)Google Scholar
  14. 14.
    Kanade, T., Cohn, J.F., Tian, Y.: Comprehensive database for facial expression analysis. In: Fourth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 46–53 (2000)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Hemant Kumar Meena
    • 1
    Email author
  • Kamlesh Kumar Sharma
    • 1
  • S. D. Joshi
    • 2
  1. 1.Department of Electronics and Communication EngineeringMalaviya National Institute of TechnologyJaipurIndia
  2. 2.Department of Electrical EngineeringIndian Institute of Technology DelhiNew DelhiIndia

Personalised recommendations