Building Large Scale 3D Face Database for Face Analysis
Yuxiao Hu1
, Zhenqiu Zhang1
, Xun Xu1
, Yun Fu1
and Thomas S. Huang1 
| (1) |
Beckman Institute, University of Illinois at Urbana-Champaign, 405 North Mathews Avenue, Urbana, IL 61801, USA |
Abstract
We propose to build a large scale 3D face database with dense correspondence for variant face analysis research purposes.
Large scale means that the number of subjects in the database is more than 400, which is, to our best knowledge, the biggest
one at this time. 3D face means that we provide both the texture and shape of human faces, which is also balanced in gender
and race. Dense correspondence means that the key facials points with semantic meanings are carefully labeled and aligned
among different faces, which can be used for a broad range of face analysis tasks. We provide the data description, data collection
schema and the post-processing methods to help the usage of the data and future extension. More and more data is still being
collected and processed to enlarge the extensive 3D face database. The proposed face database provides solid ground truth
for human face related tasks such as alignment, tracking, recognition and animation, etc.
This work is supported by NSF Grant CCF 04-26627.
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