LAFTER: lips and face real time tracker

Author

Oliver, Nuria ; Pentland, Alex P. ; Bérard, François

Author_Institution

Media Lab., MIT, Cambridge, MA, USA

fYear

1997

fDate

17-19 Jun 1997

Firstpage

123

Lastpage

129

Abstract

This paper describes an active-camera real-time system for tracking, shape description, and classification of the human face and mouth using only an SGI Indy computer. The system is based on use of 2-D blob features, which are spatially-compact clusters of pixels that are similar in terms of low-level image properties. Patterns of behavior (e.g., facial expressions and head movements) can be classified in real-time using Hidden Markov Model (HMM) methods. The system has been tested on hundreds of users and has demonstrated extremely reliable and accurate performance. Typical classification accuracies are near 100%

Keywords

face recognition; hidden Markov models; image classification; image sequences; 2-D blob features; LAFTER; SGI Indy computer; active-camera real-time system; classification accuracies; facial expressions; head movements; hidden Markov model; human face; lips and face real time tracker; shape description; spatially-compact clusters; tracking; Face; Head; Hidden Markov models; Humans; Lips; Mouth; Pixel; Real time systems; Shape; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on

Conference_Location

San Juan

ISSN

1063-6919

Print_ISBN

0-8186-7822-4

Type

conf

DOI

10.1109/CVPR.1997.609309

Filename

609309