FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
A Unified Framework for Gesture Recognition and Spatiotemporal Gesture Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for hand gesture recognition using relief
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Hand gesture recognition using depth data
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Combining RGB and ToF cameras for real-time 3D hand gesture interaction
WACV '11 Proceedings of the 2011 IEEE Workshop on Applications of Computer Vision (WACV)
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hi-index | 0.00 |
This paper presents a mixed hand gesture interaction system in virtual environment, in which "mixed" means static and dynamic hand gestures are combined for both navigation and object manipulation. Firstly, a simple average background model and skin color are used for hand area segmentation. Then a state-based spotting algorithm is employed to automatically identify two types of hand gestures. A voting-based method is used for quick classification of static gestures. And we use the hidden Markov model (HMM) to recognize dynamic gestures. Since the training of HMM requires the consistency of the training data, outputted by the feature extraction, a data aligning algorithm is raised. Through our mixed hand gesture system, users can perform complicated operating commands in a natural way. The experimental results demonstrate that our methods are effective and accurate.