Visual analysis of high DOF articulated objects with application to hand tracking
Visual analysis of high DOF articulated objects with application to hand tracking
Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Finding Pose of Hand in Video Images: A Stereo-Based Approach
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
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The Journal of Machine Learning Research
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The Journal of Machine Learning Research
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ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Tracking Articulated Hand Motion with Eigen Dynamics Analysis
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Level Set Evolution without Re-Initialization: A New Variational Formulation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Model-Based Hand Tracking Using a Hierarchical Bayesian Filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Pose Estimation from a Planar Target
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-Dimensional Shape Knowledge for Joint Image Segmentation and Pose Tracking
International Journal of Computer Vision
ZigBee Wireless Networks and Transceivers
ZigBee Wireless Networks and Transceivers
Robust Real-Time Visual Tracking Using Pixel-Wise Posteriors
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Real-time hand-tracking with a color glove
ACM SIGGRAPH 2009 papers
SixthSense: Integrating information and the real world
ISMAR '09 Proceedings of the 2009 8th IEEE International Symposium on Mixed and Augmented Reality
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International Journal of Robotics Research
Smart particle filtering for 3D hand tracking
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
PWP3D: Real-Time Segmentation and Tracking of 3D Objects
International Journal of Computer Vision
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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Pattern Recognition Letters
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Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
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We propose a real-time model-based 3D hand tracker that combines image regions and the signal from an off-the-shelf 3-axis accelerometer placed on the user's hand. The visual regions allow the tracker to cope with occlusions, motion blur and background clutter, while the latter aids with the inherent silhouette-pose ambiguities. The accelerometer and tracker are synchronised by casting the calibration problem as one of principal component analysis. Based on the assumption that, often, the number of possible hand configurations is limited by the activity the hand is engaging in, we use a multiclass pose classifier to distinguish between a number of activity dependent articulated hand configurations. We demonstrate the benefits of our method, both qualitatively and quantitatively, on a variety of video sequences and hand configurations and show a proof-of-concept human computer interface based on our system.