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FSIFT based feature points for face hierarchical clustering

机译:基于FSIFT的特征点用于面部分层聚类

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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.
机译:提出了一种基于分数阶SIFT算法(FSIFT)的人脸图像聚类方法。这种新方法基于差异矩阵。通过使用为FSIFT算法检测到的关键点计算的描述符(使用非整数阶导数)来构造此矩阵。为了证明和比较所获得结果的质量,应用了相对误差率和F度量。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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