Building large scale 3D face database for face analysis

Yuxiao Hu, Zhenqiu Zhang, N. Xu, Yun Fu, Thomas S. Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 biggest1 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.

Original languageEnglish (US)
Title of host publicationMultimedia Content Analysis and Mining - International Workshop, MCAM 2007, Proceedings
PublisherSpringer
Pages343-350
Number of pages8
ISBN (Print)9783540734161
DOIs
StatePublished - Jan 1 2007
EventInternational Workshop on Multimedia Content Analysis and Mining, MCAM 2007 - Weihai, China
Duration: Jun 30 2007Jul 1 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4577 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Workshop on Multimedia Content Analysis and Mining, MCAM 2007
Country/TerritoryChina
CityWeihai
Period6/30/077/1/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint

Dive into the research topics of 'Building large scale 3D face database for face analysis'. Together they form a unique fingerprint.

Cite this