Local Zernike Moment Representation for Facial Affect Recognition

Sariyanidi E., Gunes H., Gokmen M., Cavallaro A.

24th British Machine Vision Conference, Bristol, United Kingdom, 9 - 13 September 2013 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.5244/c.27.108
  • City: Bristol
  • Country: United Kingdom
  • Istanbul Technical University Affiliated: Yes


In this paper, we propose to use local Zernike Moments (ZMs) for facial affect recognition and introduce a representation scheme based on performing non-linear encoding on ZMs via quantization. Local ZMs provide a useful and compact description of image discontinuities and texture. We demonstrate the use of this ZM-based representation for posed and discrete as well as naturalistic and continuous affect recognition on standard datasets, and show that ZM-based representations outperform well-established alternative approaches for both tasks. To the best of our knowledge, the performance we achieved on CK+ dataset is superior to all results reported to date.