Random-Profiles-Based 3D Face Recognition System

Sensors

Kim Joongrock¹  Yu Sunjin² 

[1] Department of Electrical and Electronic Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, Korea; E-Mail:;Department of Broadcasting and Film, Cheju Halla University, 38, Halladaehak-ro, Jeju-si, Jeju-do 690-708, Korea; E-Mail:

关键词: three-dimensional (3D) face modeling;    face recognition;    3D face recognition;   

DOI  :  10.3390/s140406279

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.