The computation of optical flow
ACM Computing Surveys (CSUR)
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human motion analysis: a review
Computer Vision and Image Understanding
An HMM-Based Threshold Model Approach for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for recognizing the simultaneous aspects of American sign language
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
Coupled hidden Markov models for complex action recognition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Continuous Activity Recognition with Missing Data
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Dynamic bayesian networks for information fusion with applications to human-computer interfaces
Dynamic bayesian networks for information fusion with applications to human-computer interfaces
Adaptive models for the recognition of human gesture
Adaptive models for the recognition of human gesture
Dynamic bayesian networks: representation, inference and learning
Dynamic bayesian networks: representation, inference and learning
Robust Real-Time Face Detection
International Journal of Computer Vision
Handsignals Recognition From Video Using 3D Motion Capture Data
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Recognizing Interaction Activities using Dynamic Bayesian Network
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Visual Recognition of Similar Gestures
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
A survey of skin-color modeling and detection methods
Pattern Recognition
Computer Vision and Image Understanding
Sign Language Spotting with a Threshold Model Based on Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
HMM-Based gait recognition with human profiles
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Continuous hand gesture segmentation and co-articulation detection
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Understanding hand gestures using approximate graph matching
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Identification of humans using gait
IEEE Transactions on Image Processing
Improving of gesture recognition using multi-hypotheses object association
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
A comparison of 3D hand gesture recognition using dynamic time warping
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
A biological and real-time framework for hand gestures and head poses
UAHCI'13 Proceedings of the 7th international conference on Universal Access in Human-Computer Interaction: design methods, tools, and interaction techniques for eInclusion - Volume Part I
Online RGB-D gesture recognition with extreme learning machines
Proceedings of the 15th ACM on International conference on multimodal interaction
Rule-based trajectory segmentation for modeling hand motion trajectory
Pattern Recognition
One-shot learning gesture recognition from RGB-D data using bag of features
The Journal of Machine Learning Research
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In this paper, we propose a new method for recognizing hand gestures in a continuous video stream using a dynamic Bayesian network or DBN model. The proposed method of DBN-based inference is preceded by steps of skin extraction and modelling, and motion tracking. Then we develop a gesture model for one- or two-hand gestures. They are used to define a cyclic gesture network for modeling continuous gesture stream. We have also developed a DP-based real-time decoding algorithm for continuous gesture recognition. In our experiments with 10 isolated gestures, we obtained a recognition rate upwards of 99.59% with cross validation. In the case of recognizing continuous stream of gestures, it recorded 84% with the precision of 80.77% for the spotted gestures. The proposed DBN-based hand gesture model and the design of a gesture network model are believed to have a strong potential for successful applications to other related problems such as sign language recognition although it is a bit more complicated requiring analysis of hand shapes.