为了解决弱光环境下人脸检测问题,研究基于深度信息的人脸快速定位方法.首先,使用2D Chamfer Match方法实现人脸的快速预定位,并对定位人脸进行区域增长和增强运算;然后,使用AdaBoost算法结合扩展的Harr特征训练出弱光条件下人脸检测的强分类器,以实现准确的人脸定位.实验表明,在弱光条件下,基于深度信息实现人脸定位和过滤,可以减小搜索范围,加快检测速度,具有较强的鲁棒性和时效性.
In order to solve the problem of human face detection under weak light, a quick locating method based on the depth information by Kinect device is proposed. Firstly, 2D Chamfer Match method is used to rapidly preliminary locate the human face, and region-growing algorithm is applied on the preliminary locating face. Then, combined with extended Harr features, the AdaBoost algorithm is used to train the strong classifier under weak light, which realizes the precise face detection. The experiments show that rationally utilizing the depth information to detect the human face under the normal light can reduce the scope of the search window, which accelerates the detection speed, and the proposed method has strong robustness and timeliness.