An Improved Algorithm for Diverse AdaBoostSVM
Song Guo, Guochang Gu, Haibo Liu, Jing Shen, Changyou Li · 2009
In order to improve the training convergence speed and detection accuracy of diverse AdaBoostSVM, an improved algorithm is proposed according to the asymmetry in face detection. In the algorithm, the weight of each weak learner, which represents importance of each weak learner, is determined by the error rate and the recognition capability of the weak learner for the face samples. The results of the experiments show that the proposed algorithm could improve the training convergence speed and the detection accuracy in face detection.