AdaBoost Face Detection Based on Haar-Like Intensity Features and Multi-threshold Features

Effected by illumination and complex background, Haar-like feature values have a large change, and cannot sufficiently represent the face image texture information. By analyzing the distribution of Haar-like feature values, we propose a new type of classifiers called Haar-like intensity feature. Experimental results on some hand-labeled examples and MIT-CMU test dataset illustrate that the AdaBoost algorithm using the extensive features can reduce detection time and make higher face detection rate with fewer simple classifiers.

[1]  Harry Shum,et al.  Kullback-Leibler boosting , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[2]  Takeshi Mita,et al.  Joint Haar-like features for face detection , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[3]  Wen Gao,et al.  Novel Face Detection Method Based on Gabor Features , 2004, SINOBIOMETRICS.

[4]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[5]  Stan Z. Li,et al.  FloatBoost learning and statistical face detection , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  James M. Rehg,et al.  Fast Asymmetric Learning for Cascade Face Detection , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Yi Liu,et al.  A Novel Face Detection Method Based on Contourlet Features , 2009, ICIC.

[8]  Rainer Lienhart,et al.  Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection , 2003, DAGM-Symposium.

[9]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[10]  Yoram Singer,et al.  Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.

[11]  Kin-Man Lam,et al.  Face detection using simplified Gabor features and hierarchical regions in a cascade of classifiers , 2009, Pattern Recognit. Lett..