道路运输安全管理制度.doc

Abstract
Face detection has e the hot research topic in the field puter vision and pattern recognition. As far as early in the 1990s, people have begun to engage in the newly opened areas of face recognition research, and now more and more solution methods have been proposed. However, because of the three-dimensional rigid body feature of the face, there are still many difficulties in the multi-view face detection which would be easily affected by the intensity of light, the angle of face or the camera and the mask over the face.
To achieve the fast multi-view face detection system, the major works of this paper done as follows:
Using a double-layer multi-view face detection (MVFD) tree structure bined with the attitude estimation. Firstly, using a pre-depth classifier structure which can quickly distinguish faces and non-faces. Secondly, proposing a fast face attitude estimation algorithm which reusing the LAB feature extracting in pre-classifier and use Adaboost M1 which faces multi-label issue. The candidate windows will be send to the classifier which belongs to a face attitude, what’s more , it speeds up the overall classification rate of detection. Finally, BFS tree structure will be used to enhance the accuracy in MVFD tree.
Studying and implementing the cascade Adaboost classifier algorithm based on large-scale samples set. The traditional cascade classifier can onl