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Open AccessArticle

Random-Profiles-Based 3D Face Recognition System

1
Department of Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, Korea
2
Department of Broadcasting and Film, Cheju Halla University, 38, Halladaehak-ro, Jeju-si, Jeju-do 690-708, Korea
*
Author to whom correspondence should be addressed.
Sensors 2014, 14(4), 6279-6301; https://doi.org/10.3390/s140406279
Received: 22 January 2014 / Revised: 10 March 2014 / Accepted: 24 March 2014 / Published: 31 March 2014
(This article belongs to the Section Physical Sensors)
In this paper, a noble nonintrusive three-dimensional (3D) face modeling system for random-profile-based 3D face recognition is presented. Although recent two-dimensional (2D) face recognition systems can achieve a reliable recognition rate under certain conditions, their performance is limited by internal and external changes, such as illumination and pose variation. To address these issues, 3D face recognition, which uses 3D face data, has recently received much attention. However, the performance of 3D face recognition highly depends on the precision of acquired 3D face data, while also requiring more computational power and storage capacity than 2D face recognition systems. In this paper, we present a developed nonintrusive 3D face modeling system composed of a stereo vision system and an invisible near-infrared line laser, which can be directly applied to profile-based 3D face recognition. We further propose a novel random-profile-based 3D face recognition method that is memory-efficient and pose-invariant. The experimental results demonstrate that the reconstructed 3D face data consists of more than 50 k 3D point clouds and a reliable recognition rate against pose variation. View Full-Text
Keywords: three-dimensional (3D) face modeling; face recognition; 3D face recognition three-dimensional (3D) face modeling; face recognition; 3D face recognition
MDPI and ACS Style

Kim, J.; Yu, S.; Lee, S. Random-Profiles-Based 3D Face Recognition System. Sensors 2014, 14, 6279-6301.

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