Fast and robust 3D face matching approach

Author

Pan, Ye ; Dai, Bo ; Peng, Qicong

Author_Institution

Univ. of Electron. Sci. & Technol. of China, Chengdu, China

fYear

2010

fDate

9-11 April 2010

Firstpage

195

Lastpage

198

Abstract

We present a novel three-dimensional (3D) face matching approach in this paper. First, 3D facial scans are segmented and four feature points of each face are detected for rough alignment the by Absolute Orientation method. Then a modified Iterative Closest Point (ICP) algorithm is employed for range image registration. A Simulated Annealing (SA) based approach with the Surface Interpenetration Measure (SIM), as similarity measure, is used for final matching. Our experimental results on the Face Recognition Grand Challenge (FRGC) v2 database show that the proposed method could achieve 99% rank one recognition performance at 0.001 False Acceptance Rate (FAR) on all neutral expression with noisy data.

Keywords

computer vision; face recognition; image matching; image registration; image segmentation; 3D facial scans; absolute orientation method; face recognition grand challenge v2 database; false acceptance rate; image registration; iterative closest point; rough alignment; simulated annealing; surface interpenetration measure; three-dimensional face matching; Face detection; Face recognition; Image registration; Image segmentation; Iterative algorithms; Iterative closest point algorithm; Robustness; Rough surfaces; Simulated annealing; Surface roughness; 3D Face Matching; Absolute Orientation; FRGC; ICP; Simulated Annealing; Surface Interpenetration Measure;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Signal Processing (IASP), 2010 International Conference on

Conference_Location

Zhejiang

Print_ISBN

978-1-4244-5554-6

Electronic_ISBN

978-1-4244-5556-0

Type

conf

DOI

10.1109/IASP.2010.5476132

Filename

5476132