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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/23001

Title: Novel approach to enhance face recognition using depth maps
Authors: Saleh, Yaser
Edirisinghe, Eran A.
Keywords: Face recognition
Image recognition
Benchmark testing
Issue Date: 2016
Publisher: © IEEE
Citation: SALEH, Y. and EDIRISINGHE, E.A., 2016. Novel approach to enhance face recognition using depth maps. Presented at the 23rd International Conference on Systems, Signals and Image Processing (IWSSIP), Bratislava, 23-25th May.
Abstract: Face recognition, although being a popular area of research and study, still has many challenges, and with the appearance of the Microsoft Kinect device, new possibilities of research were uncovered, one of which is face recognition using the Kinect. With the goal of enhancing face recognition, this paper is aiming to prove how depth maps, since not effected by illumination, can improve face recognition with a benchmark algorithm based on the Eigenface. This required some experiments to be carried out, mainly in order to check if algorithms created to recognize faces using normal images can be as effective if not more effective with depth map images. The OpenCV Eigenface algorithm implementation was used for the purpose of training and testing both normal and depth-map images. Finally, results of the experiments are presented to prove the ability of the tested algorithm to function with depth maps, also, proving the capability of depth maps face recognition’s task in poor illumination.
Description: Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Version: Accepted
DOI: 10.1109/IWSSIP.2016.7502699
URI: https://dspace.lboro.ac.uk/2134/23001
Publisher Link: http://dx.doi.org/10.1109/IWSSIP.2016.7502699
Appears in Collections:Conference Papers and Presentations (Computer Science)

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