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face-detection-methods
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A contourlet-based face detection method in color images
, Article 3rd IEEE International Conference on Signal Image Technologies and Internet Based Systems, SITIS'07, Jiangong Jinjiang, Shanghai, 16 December 2007 through 18 December 2007 ; 2007 , Pages 727-732 ; 9780769531229 (ISBN) ; Jamzad, M ; Sharif University of Technology
2007
Abstract
The first step of any face processing system is detecting the location in images where faces are present. In this paper we present an upright frontal face detection system based on the multi-resolution analysis of the face. In this method firstly, skin-color information is used to detect skin pixels in color images; then, the skin-region blocks are decomposed into frequency sub-bands using contourlet transform. Features extracted from sub-bands are used to detect face in each block. A multi-layer perceptrone (MLP) neural network was trained to do this classification. To decrease false positive detection we use eyes and lips template matching. These templates achieved by averaging...
AdaBoost-based face detection in color images with low false alarm
, Article ICCMS 2010 - 2010 International Conference on Computer Modeling and Simulation, 22 January 2010 through 24 January 2010, Sanya ; Volume 2 , 2010 , Pages 107-111 ; 9780769539416 (ISBN) ; Kasaei, S ; Sharif University of Technology
2010
Abstract
In this paper, we have proposed a new face detection method which combines the AdaBoost algorithm with skin color information and support vector machine (SVM). First, a cascade classifier based on AdaBoost is used to detect faces in images. Due to noise and illumination changes some nonfaces might be detected too, therefore we have used a skin color model in the YCbCr color space to remove some of the detected nonfaces. Finally, we have utilized SVM to detect faces more accurately. Experimental results show that the performance of the proposed method is higher than the basic AdaBoost in the sense of detecting fewer nonfaces