FSIFT based feature points for face hierarchical clustering

G. Sarwas, S. Skoneczny
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引用次数: 2

Abstract

In this paper a method for clustering face images based on fractional order SIFT algorithm (FSIFT) is presented. This new approach is based on the dissimilarity matrix. This matrix is constructed by using descriptors calculated for keypoints detected by FSIFT algorithm using derivatives of non integer order. To proof and compared the quality of achieved results the relative error ratio and the F-measure were applying. The final scores of experiments were compared with hierarchical clustering methods based on SIFT and SURF detectors.
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基于FSIFT的人脸特征点分层聚类
提出了一种基于分数阶SIFT算法的人脸图像聚类方法。这种新方法是基于不相似矩阵的。该矩阵是利用非整数阶导数对FSIFT算法检测到的关键点计算的描述子来构造的。应用相对错误率和f -测度来证明和比较所获得结果的质量。将实验的最终分数与基于SIFT和SURF检测器的分层聚类方法进行比较。
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