Title :
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
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;
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
DOI :
10.1109/RATFG.1999.799236
