Adaboost-Based Face Detection Method in Hierarchical Feature Spaces
Li San · 2007
In the face detection method of Viola and Jones,the weak classifiers based on the feature of Haar-like are very weak in the late stages of the cascade classifier training.Aiming at this problem, a new face detection method based on Adaboost in hierarchical feature spaces is developed.In this method,the performance of the weak classifiers is improved through the training in local and global feature spaces.The experimental results show that the performance of this modified method is better than that of the current state-of-the-art system for the high accurate detection rates and the small false alarm number of the system.