3D face recognition in the Fourier domain using deformed circular curves

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• 作者：Deokwoo Lee ; Hamid Krim
• 关键词：Face recognition ; Classification ; Deformed circular curves ; Geodesic distance ; Fourier Transform ; Dimensionality reduction
• 刊名：Multidimensional Systems and Signal Processing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：28
• 期：1
• 页码：105-127
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Circuits and Systems; Electrical Engineering; Signal,Image and Speech Processing; Artificial Intelligence (incl. Robotics);
• 出版者：Springer US
• ISSN：1573-0824
• 卷排序：28

文摘

One of the most significant problems in image and vision applications is the efficient representation of a target image containing a large amount of data with high complexity. The ability to analyze high dimensional signals in a lower dimension without losing their information, has been crucial in the field of image processing. This paper proposes an approach to 3D face recognition using dimensionality reduction based on deformed circular curves, on the shortest geodesic distances, and on the properties of the Fourier Transform. Measured geodesic distances information generates a matrix whose entities are geodesic distances between the reference point and an arbitrary point on a 3D object, and an one-dimensional vector is generated by reshaping the matrix without losing the original properties of the target object. Following the property of the Fourier Transform, symmetry of the magnitude response, the original signal can be analyzed in the lower dimensional space without loss of inherent characteristics. This paper mainly deal with the efficient representation and recognition algorithm using deformed circular curves and the simulation shows promising result for recognition of geometric face information.