Proposed optimization for AdaBoost-based face detection

Jiu Xu*, Satoshi Goto

*Corresponding author for this work

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

3 Citations (Scopus)


In this paper, a novel approach is proposed for face detection in still image based on the AdaBoost algorithm. First, face candidates are detected by AdaBoost Algorithm. Since a lot of influence might exist, such as size of the image, illumination and noise, some non-faces windows might also be detected as face candidates, or some faces might be missed. In order to solve these problems and get better performances, we take use of skin color information in the YCbCr color space together with the edge information of the color image. In this way, we are able to remove some non-faces that have been wrongly detected as faces and add some possible missed faces as well. Experimental results show that the hit rate could be improved and false alarm could also be reduced by this method.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 2011
Event3rd International Conference on Digital Image Processing, ICDIP 2011 - Chengdu
Duration: 2011 Apr 152011 Apr 17


Other3rd International Conference on Digital Image Processing, ICDIP 2011


  • AdaBoost
  • canny edge detection
  • elliptical model
  • skin color segmentation

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics


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