Automatic detection of facial midline as a guide for facial feature extraction

Nozomi Nakao, Wataru Oyama, Tetsushi Wakabayashi, Fumitaka Kimura

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

Abstract

We propose a novel approach for the detection of the facial midline from a frontal face image. The use of a midline as a guide reduces the computation time required for facial feature extraction (FFE) because midline is able to restrict multi-dimensional searching process into one-dimensional search. The proposed method detects facial midline from the edge image as the symmetry axis using a new application of the the generalized Hough transformation to detect the symmetry axis. Experimental results on the FERET database indicate that the proposed algorithm can accurately detect facial midline over many different scales and rotation. The total computational time for facial feature extraction has been reduced by a factor of 280 using midline detected by this method.

Original languageEnglish
Title of host publicationProceedings of the 7th International Workshop on Pattern Recognition in Information Systems PRIS 2007; In Conjunction with ICEIS 2007
Pages119-128
Number of pages10
Publication statusPublished - Dec 1 2007
Externally publishedYes
Event7th International Workshop on Pattern Recognition in Information Systems PRIS 2007; In Conjunction with ICEIS 2007 - Funchal, Madeira, Portugal
Duration: Jun 12 2007Jun 13 2007

Other

Other7th International Workshop on Pattern Recognition in Information Systems PRIS 2007; In Conjunction with ICEIS 2007
CountryPortugal
CityFunchal, Madeira
Period6/12/076/13/07

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All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Information Systems

Cite this

Nakao, N., Oyama, W., Wakabayashi, T., & Kimura, F. (2007). Automatic detection of facial midline as a guide for facial feature extraction. In Proceedings of the 7th International Workshop on Pattern Recognition in Information Systems PRIS 2007; In Conjunction with ICEIS 2007 (pp. 119-128)