使用关键点信息改进弹性匹配人脸识别算法

本文提出了一种增加经典弹性匹配算法对强背景干扰鲁棒性的算法.人脸的自动识别有着广泛的应用前景,弹性匹配是其中的一种重要算法,并有着相对于其他方法更高的鲁棒性,但其并不能有效地防止强背景干扰的影响.本文的主要思路是将局部信息和整体信息相结合,利用没有受到背景干扰影响的局部关键点的位置信息来对基于整体信息的经典弹性匹配方法进行改进.实验结果表明,本文提出的算法有效地提高了弹性匹配识别算法的鲁棒性.

Using Key Points to Improve Elastic Matching in Face Recognition

An algorithm to improve the robustness of elastic matching in face recognition is proposed when it is strongly disturbed by the background. Automatic human face recognition has various applications. Elastic matching is an important face recognition algorithm, and it has higher robustness compared to other algorithms. But it also cannot deal with the disturbance from background effectively . The basic point of our algorithm is combining local information and global information together and using the local information undisturbed by the background to improve elastic matching algorithm. Experimental results demonstrate that the proposed method has improved the robustness of elastic matching.