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Download fileNovel approach to enhance face recognition using depth maps
conference contribution
posted on 2016-10-28, 14:00 authored by Yaser Saleh, Eran EdirisingheFace 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.
History
School
- Science
Department
- Computer Science
Published in
Welcome to Bratislava to The 23rd International Conference on Systems, Signals and Image Processing, IWSSIP 2016Citation
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.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publication date
2016Notes
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2157-8702Publisher version
Language
- en