A quantitative comparison of 3D face databases for 3D face recognition

Dirk Smeets; Jeroen Hermans; Dirk Vandermeulen; Paul Suetens

doi:10.1117/12.883427

17 May 2011 A quantitative comparison of 3D face databases for 3D face recognition

Dirk Smeets, Jeroen Hermans, Dirk Vandermeulen, Paul Suetens

Proceedings Volume 8029, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII; 80291L (2011) https://doi.org/10.1117/12.883427
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

During the last decade research in face recognition has shifted from 2D to 3D face representations. The need for 3D face data has resulted in the advent of 3D databases. In this paper, we first give an overview of publicly available 3D face databases containing expression variations, since these variations are an important challenge in today's research. The existence of many databases demands a quantitative comparison of these databases in order to compare more objectively the performances of the various methods available in literature. The ICP algorithm is used as baseline algorithm for this quantitative comparison for the identification and verification scenario, allowing to order the databases according to their inherent difficulty. Performance analysis using the rank 1 recognition rate for identification and the equal error rate for verification reveals that the FRGC v2 database can be considered as the most challenging. Therefore, we recommend to use this database further as reference database to evaluate (expression-invariant) 3D face recognition algorithms. As second contribution, the main factors that influence the performance of the baseline technique are determined and attempted to be quantified. It appears that (1) pose variations away from frontality degrade performance, (2) expression types affect results, (3) more intense expressions degrade recognition, (4) an increasing number of expressions decreases performance and (5) the number of gallery subjects degrades performace. A new 3D face recognition algorithm should be evaluated for all these factors.

Citation Download Citation

Dirk Smeets, Jeroen Hermans, Dirk Vandermeulen, and Paul Suetens "A quantitative comparison of 3D face databases for 3D face recognition", Proc. SPIE 8029, Sensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring; and Biometric Technology for Human Identification VIII, 80291L (17 May 2011); https://doi.org/10.1117/12.883427

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Databases

Facial recognition systems

Detection and tracking algorithms

3D scanning

Algorithm development

3D image processing

Error analysis

Show All Keywords

Keywords/Phrases

Search In:

Publication Years