A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curvature scale space image in shape similarity retrieval
Multimedia Systems
A System for Person-Independent Hand Posture Recognition against Complex Backgrounds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Analysis of Hand Posture
IEEE Computer Graphics and Applications
Model-based tracking of self-occluding articulated objects
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Real-Time 3-D Hand Posture Estimation Based on 2-D Appearance Retrieval Using Monocular Camera
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Tracking Articulated Hand Motion with Eigen Dynamics Analysis
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Shape context and chamfer matching in cluttered scenes
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
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We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily the continuous-based tracking which is replaced by the discrete one, to obtain model re-initializations when necessary. We use the error in the continuous tracking to learn off-line, based on SVMs, when the continuous-based tracking fails and switch between the two methods. We develop a novel discrete method for 3D shape configuration estimation, which utilizes both frame and multi-frame features, taking into account the most recent input frames, using a time-window. We therefore overcome the error accumulation over time, that most continuous methods suffer from and simultaneously reduce the discrete method's complexity and prevent possible multiple solutions in shape estimation. We demonstrate the power of our framework in complex hand tracking sequences with large rotations, articulations, lighting changes and occlusions.