The Strength of Weak Learnability
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
IEEE Computer Graphics and Applications
Gesture VR: vision-based 3D hand interace for spatial interaction
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
ACM Transactions on Computer-Human Interaction (TOCHI)
Machine Learning
Finger Track - A Robust and Real-Time Gesture Interface
AI '97 Proceedings of the 10th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Toward the use of gesture in traditional user interfaces
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Manipulative Hand Gesture Recognition Using Task Knowledge for Human Computer Interaction
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
VR '03 Proceedings of the IEEE Virtual Reality 2003
Robust Real-Time Face Detection
International Journal of Computer Vision
Visual touchpad: a two-handed gestural input device
Proceedings of the 6th international conference on Multimodal interfaces
Visual tracking of bare fingers for interactive surfaces
Proceedings of the 17th annual ACM symposium on User interface software and technology
SmartCanvas: a gesture-driven intelligent drawing desk system
Proceedings of the 10th international conference on Intelligent user interfaces
Regression-based Hand Pose Estimation from Multiple Cameras
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Vision-based hand pose estimation: A review
Computer Vision and Image Understanding
Tracking of Fingertips and Centers of Palm Using KINECT
CIMSIM '11 Proceedings of the 2011 Third International Conference on Computational Intelligence, Modelling & Simulation
Real-time human pose recognition in parts from single depth images
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Efficient regression of general-activity human poses from depth images
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Development of human-computer interaction methods tends to exploit more and more natural human activities like thoughts, body posture or hands gesticulation. While most of authors improve whole body tracking this paper concentrates on hand's poses analysis. Due to the usage of the depth image based object recognition approach to hand pose estimation a very precise method was obtained. Additionally thanks to decision forest implemented on GPU a real-time processing is possible.