Loading...

AdaBoost-based face detection in color images with low false alarm

Arjomand Inalou, S ; Sharif University of Technology | 2010

713 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/ICCMS.2010.287
  3. Publisher: 2010
  4. Abstract:
  5. 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
  6. Keywords:
  7. Skin color features ; Support Vector Machine (SVM) ; AdaBoost ; AdaBoost algorithm ; Cascade classifiers ; Color images ; Color space ; Face detection ; Face detection methods ; False alarms ; Illumination changes ; Skin color ; Skin color models ; Skin-color information ; Color ; Computer simulation ; Face recognition ; Image enhancement ; Support vector machines ; Adaptive boosting
  8. Source: 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)
  9. URL: http://ieeexplore.ieee.org/document/5421116