Pose invariant thermal face recognition using patch-wise self-similarity features

Sandip Joardar, Dwaipayan Sen, Diparnab Sen, Arnab Sanyal, A. Chatterjee
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引用次数: 7

Abstract

This paper presents a Pose Invariant Face Recognition algorithm for pose-variance in face databases, which is one of the toughest challenges of any face recognition based biometrics, using a novel feature extraction technique. The feature extraction of the raw images is based upon a novel patch-wise self-similarity measure within an image. The algorithm has been tested upon a Far-infrared (FIR) imaging based Face database called the JU-FIR-F1: FIR Face Database that has been developed in the Electrical Instrumentation and Measurement Laboratory, Electrical Engineering Department, Jadavpur University, Kolkata, India. The results obtained through extensive experimentation clearly demonstrate the superiority of the proposed method over the existing algorithms.
基于自相似特征的姿态不变热人脸识别
本文提出了一种姿态不变人脸识别算法,该算法采用一种新的特征提取技术,用于人脸数据库中的姿态方差,这是任何基于人脸识别的生物特征识别中最棘手的挑战之一。原始图像的特征提取是基于一种新的图像内的自相似度度量。该算法已经在一个基于远红外(FIR)成像的人脸数据库上进行了测试,该数据库被称为JU-FIR-F1: FIR人脸数据库,该数据库由印度加尔各答Jadavpur大学电气工程系电气仪器和测量实验室开发。通过大量的实验得到的结果清楚地表明,所提出的方法优于现有的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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