Face Shape Classification Based on Active Shape Model and K-nearest Neighbor Algorithm
Face Shape Classification Based on Active Shape Model and K-nearest Neighbor Algorithm
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发表时间：
2011
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通讯作者：
Tu Yi
中科院分区：
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作者：
Tu Yi
针对人脸特征分类问题，提出了一种基于主动形状模型（ASM）和K近邻算法的人脸分类算法，该算法利用ASM算法提取人脸的特征点，对所有特征点进行归一化处理，并计算特征点与每类样本之间的Hausdorff距离，利用K-实验结果表明，该算法具有较高的分类精度和速度，且易于实现。
Aiming at the problem of face feature classification,this paper proposes a new face classification algorithm based on Active Shape Model(ASM) and K-nearest neighbor algorithm.It extracts feature points of face by ASM algorithm,normalizes all feature points,and computes Hausdorff distance between feature points and every sample of each class.The face is classified by K-nearest neighbor algorithm with the Hausdorff distance computed.Experimental results show that the algorithm has high classification accuracy and speed,and it is easy to realize.