Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning-based dynamic coupling of discrete and continuous trackers
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Real-time hand tracking using a mean shift embedded particle filter
Pattern Recognition
Smart particle filtering for high-dimensional tracking
Computer Vision and Image Understanding
Resolving hand over face occlusion
Image and Vision Computing
Vision-based hand pose estimation: A review
Computer Vision and Image Understanding
Hand Motion Prediction for Distributed Virtual Environments
IEEE Transactions on Visualization and Computer Graphics
Navigating a 3D virtual environment of learning objects by hand gestures
International Journal of Advanced Media and Communication
Research on Sampling Methods in Particle Filtering Based upon Microstructure of State Variable
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Towards Communicative Face Occlusions: Machine Detection of Hand-over-Face Gestures
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
HandPuppet3D: Motion capture and analysis for character animation
Artificial Intelligence Review
Hand posture estimation in complex backgrounds by considering mis-match of model
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Visual affect recognition
Silhouette area based similarity measure for template matching in constant time
AMDO'10 Proceedings of the 6th international conference on Articulated motion and deformable objects
Segmentation-free, area-based articulated object tracking
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
3D hand pose reconstruction with ISOSOM
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Real-time viewpoint-invariant hand localization with cluttered backgrounds
Image and Vision Computing
Resolving hand over face occlusion
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
Dynamic data driven coupling of continuous and discrete methods for 3d tracking
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
3D hand tracking for human computer interaction
Image and Vision Computing
A brief review of vision based hand gesture recognition
CSECS'11/MECHANICS'11 Proceedings of the 10th WSEAS international conference on Circuits, Systems, Electronics, Control & Signal Processing, and Proceedings of the 7th WSEAS international conference on Applied and Theoretical Mechanics
3D articulated hand tracking based on behavioral model
Transactions on Edutainment VIII
Combining marker-based mocap and RGB-D camera for acquiring high-fidelity hand motion data
EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Combining marker-based mocap and RGB-D camera for acquiring high-fidelity hand motion data
Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Video-based hand manipulation capture through composite motion control
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
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This paper introduces the concept of eigen-dynamics andproposes an eigen dynamics analysis (EDA) method to learnthe dynamics of natural hand motion from labelled sets ofmotion captured with a data glove. The result is parameterizedwith a high-order stochastic linear dynamic system(LDS) consisting of five lower-order LDS. Each correspondingto one eigen-dynamics. Based on the EDA model, weconstruct a dynamic Bayesian network (DBN) to analyzethe generative process of a image sequence of natural handmotion. Using the DBN, a hand tracking system is implemented.Experiments on both synthesized and real-worlddata demonstrate the robustness and effectiveness of thesetechniques.