A statistical upper body model for 3D static and dynamic gesture recognition from stereo sequences

IEEE International Conference on Image Processing

Volumn 3, Issue , 2001, Pages 286-289

  Nefian, A V ^a   Grzeszczuk, R ^a   Eruhimov, V ^a  

^a INTEL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; HUMAN COMPUTER INTERACTION; IMAGE SEGMENTATION; MARKOV PROCESSES; THREE DIMENSIONAL;

OBSERVATION VECTORS; STEREO SEQUENCES;

GESTURE RECOGNITION;

EID: 0035164228     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. Stereo based gesture recognition invariant to 3D pose and lighting
2. Real-time context-based gesture recognition using HMM automation
3. Tracking self-occluding articulated objects in dense disparity maps
4. Detection and estimation of pointing gestures in dense disparity maps
5. Hand gesture recognition using input-output hidden markov models
6. Crane gesture recognition using pseudo 3-D hidden Markov models
7. Fast and accurate 3D gesture recognition interface
8. A wearable computer based american sign language recognizer
9. Real-time gesture recognition using KL expansion of image sequence
10. Human computer interface for gesture-based editing system