Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5021
Title: Human recognition using 3D ear images
Authors: Prakash, Surya
Keywords: Biometrics;3D ear recognition;Generalized procrustes analysis;Human recognition;Iterative closest point;Iterative Closest Points;Local feature;Matching techniques;University of Notre Dame;Face recognition
Issue Date: 2014
Publisher: Elsevier
Citation: Prakash, S., & Gupta, P. (2014). Human recognition using 3D ear images. Neurocomputing, 140, 317-325. doi:10.1016/j.neucom.2014.03.007
Abstract: This paper proposes an ear recognition technique which makes use of 3D along with co-registered 2D ear images. It presents a two-step matching technique to compare two 3D ears. In the first step, it computes salient 3D data points from 3D ear images with the help of local 2D feature points of co-registered 2D ear images. Subsequently, it uses these salient 3D points to coarsely align 3D ear images. In the second step, it performs final matching of coarsely aligned 3D ear images by using a Generalized Procrustes Analysis (GPA) and Iterative Closest Point (ICP) based matching technique (GPA-ICP). The proposed technique has been tested on 1780 images of 404 subjects (two or more images per subject) of University of Notre Dame public database-Collection J2 (UND-J2) which consists of co-registered 2D and 3D ear images with scale and pose variations. It has achieved a verification accuracy of 98.30% with an equal error rate of 1.8%. © 2014 Elsevier B.V.
URI: https://doi.org/10.1016/j.neucom.2014.03.007
https://dspace.iiti.ac.in/handle/123456789/5021
ISSN: 0925-2312
Type of Material: Journal Article
Appears in Collections:Department of Computer Science and Engineering

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