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Volume 12 Issue 4
August  2015
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Ying-Ying Zheng and Jun Yao. Multi-angle Face Detection Based on DP-Adaboost. International Journal of Automation and Computing, vol. 12, no. 4, pp. 421-431, 2015. https://doi.org/10.1007/s11633-014-0872-8
Citation: Ying-Ying Zheng and Jun Yao. Multi-angle Face Detection Based on DP-Adaboost. International Journal of Automation and Computing, vol. 12, no. 4, pp. 421-431, 2015. https://doi.org/10.1007/s11633-014-0872-8
shu

Multi-angle Face Detection Based on DP-Adaboost

doi: 10.1007/s11633-014-0872-8

  • School of Mechanical and Electronic Engineering and Automation, Shanghai University, Shanghai 200072, China

  • Received Date: 2013-09-30
  • Rev Recd Date: 2014-05-05
  • Publish Date: 2015-08-01
    Abstract
  • Although important progresses have been already made in face detection, many false faces can be found in detection results and false detection rate is influenced by some factors, such as rotation and tilt of human face, complicated background, illumination, scale, cloak and hairstyle. This paper proposes a new method called DP-Adaboost algorithm to detect multi-angle human face and improve the correct detection rate. An improved Adaboost algorithm with the fusion of frontal face classifier and a profile face classifier is used to detect the multi-angle face. An improved horizontal differential projection algorithm is put forward to remove those non-face images among the preliminary detection results from the improved Adaboost algorithm. Experiment results show that compared with the classical Adaboost algorithm with a frontal face classifier, the textual DP-Adaboost algorithm can reduce false rate significantly and improve hit rate in multi-angle face detection.

     

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