A face Detection Based on a Weighted Least Squares Error Boosting Algorithm
HU Shi-ming · Journal of Jiaying University · 2008
Recently AdaBoost algorithm was successfully applied to solve the problems of face detection.This paper presents a face detection based on a weighted least squares error boosting algorithm.First this method trains the weak hypothesis with the minimum weighted least squares error at each iteration.What differs from the original AdaBoost is that each weak hypothesis generates not only predicted classifications,but also estimate the confidence-rated of each of its predictions.Then,The final hypothesis is combination of the weak hypotheses whose predictions are confidence-rated.Experimental results prove that the classifiers based on a weighted least squares error boosting algorithm have a higher detection rate but a lower false positive rate.