Deformable model and HMM-based tracking, analysis and recognition of gestures and faces

Author

Metaxas, Dimitris

Author_Institution

Dept. of Comput. & Inf. Sci., Pennsylvania Univ., Philadelphia, PA, USA

fYear

1999

fDate

1999

Firstpage

136

Lastpage

140

Abstract

In this paper we present a framework for the shape and motion estimation and recognition of faces and gestures. We first present physics-based modeling techniques for the 3D shape and motion estimation of humans based on single and multiple views as well as the integration of visual cues such as edges and optical flow. We then demonstrate that the reliable recognition of gesture and American Sign Language (ASL) in particular, requires the use of 3D tracking data, ASL phonology and modifications to the traditional use of Hidden Markov Models

Keywords

face recognition; gesture recognition; image sequences; motion estimation; tracking; American Sign Language; HMM-based tracking; deformable model; faces recognition; gestures recognition; hidden Markov models; motion estimation; optical flow; physics-based modeling; visual cues; Biomedical optical imaging; Deformable models; Face recognition; Handicapped aids; Hidden Markov models; Humans; Image sequences; Integrated optics; Motion estimation; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, 1999. Proceedings. International Workshop on

Conference_Location

Corfu

Print_ISBN

0-7695-0378-0

Type

conf

DOI

10.1109/RATFG.1999.799236

Filename

799236