Face occlusion detection by using B-spline active contour and skin color information

Gahyun Kim, Jae Kyu Suhr, Ho Gi Jung, Jaihie Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Citations (Scopus)

Abstract

This paper proposes a face occlusion verification method for an automated teller machine (ATM) application. The proposed method mainly consists of three steps. Firstly, a head and shoulder shape is detected by applying B-spline active contour to motion edges. This motion edge is generated by a kurtosis-based frame selection and distance transformation-based motion edge detection. Secondly, a face area is estimated by fitting an ellipse to the detected head and shoulder shape. Finally, occlusion of the face area is determined by measuring skin color area ratio (SCAR) of whole face area and facial component areas. Experimental results show that the proposed head and shoulder detection method has 94.8% detection rate even though there are various types of severe occlusions in faces, and the proposed occlusion verifier has 86.7% verification rate.

Original languageEnglish
Title of host publication11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
Pages627-632
Number of pages6
DOIs
Publication statusPublished - 2010 Dec 1
Event11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 - Singapore, Singapore
Duration: 2010 Dec 72010 Dec 10

Publication series

Name11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010

Other

Other11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
CountrySingapore
CitySingapore
Period10/12/710/12/10

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering

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    Kim, G., Suhr, J. K., Jung, H. G., & Kim, J. (2010). Face occlusion detection by using B-spline active contour and skin color information. In 11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 (pp. 627-632). [5707762] (11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010). https://doi.org/10.1109/ICARCV.2010.5707762