非限定条件下无约束的多姿态人脸关键特征自动识别算法

Automatic Recognition Algorithm for Unconstrained Multi-pose Face Key Features under Unqualified Conditions

多姿态人脸关键特征的自动识别,对处理人脸数据库中的图像具有重要意义。为了保证人脸关键特征被准确识别,需要对人脸关键特征进行提取。传统算法对多姿态人脸关键特征进行自动识别时有效性差、识别率低、效率低。为此,文中提出了一种基于向量机的多姿态人脸关键特征自动识别算法,利用相机的焦距将人脸关键特征图像的三维坐标表示出来,计算出多姿态人脸关键特征的三维信息。利用滤波器处理多姿态人脸的关键特征并对其进行提取,最后根据向量机的权值,对人脸关键特征的目标函数和特征中的噪声进行分析,计算人脸自动识别的条件概率和迭代次数,实现非限定条件下无约束多姿态人脸关键特征的自动识别。实验结果表明,所提算法能够对多姿态人脸关键特征进行自动识别,并且具有较高的识别率。

Automatic recognition of multi-pose faces key features is of great significance to the processing of images in face database.In order to ensure that face key features are accurately recognized,it is necessary to extract key features of the face.When the traditional algorithm is used to automatically recognize multi-pose face key features,the obtained face images are of poor efficiency,low recognition rate and low efficiency.This paper presented an automatic multi-pose face feature recognition algorithm based on vector machine.The 3D coordinate of the face key feature image is represented by the focal length of the camera, and the 3D information of the multi-pose face key feature is calculated. Filter is used to deal with multi-pose face key features.Finally, according to the weight of the vector machine,this paper analyzed the target function and the noise of face key features,calculated the condition probability and the iteration number of the face automatic recognition,and realized the automatic recognition of the key features of unconstrained multi-pose face under the unqualified condition.Experiment results show that the proposed algorithm can be used to automatically identifiy the multi-pose face key features,and has high recognition rate and recognition efficiency.