A note on the gradient of a multi-image
Computer Vision, Graphics, and Image Processing - Lectures notes in computer science, Vol. 201 (G. Goos and J. Hartmanis, Eds.)
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region-based strategies for active contour models
International Journal of Computer Vision
Recursive implementation of the Gaussian filter
Signal Processing
Model-Based Estimation of 3D Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D articulated models and multiview tracking with physical forces
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Steerable-Scalable Kernels for Edge Detection and Junction Analysis
ECCV '92 Proceedings of the Second European Conference on Computer Vision
3-D model-based tracking of humans in action: a multi-view approach
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Twist Based Acquisition and Tracking of Animal and Human Kinematics
International Journal of Computer Vision
Learning to track 3D human motion from silhouettes
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Implicit Surfaces Make for Better Silhouettes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Tracking with the kinematics of extremal contours
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Boundary conditions for Young-van Vliet recursive filtering
IEEE Transactions on Signal Processing - Part I
Fast anisotropic Gauss filtering
IEEE Transactions on Image Processing
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This paper addresses the problem of articulated motion tracking from image sequences. We describe a method that relies on both an explicit parameterization of the extremal contours and on the prediction of the human boundary edges in the image. We combine extremal contour prediction and edge detection in a non linear minimization process. The error function that measures the discrepancy between observed image edges and predicted model contours is minimized using an analytical expression of the Jacobian that maps joint velocities onto extremal contour velocities. In practice, we model people both by their geometry (truncated elliptic cones) and their articulated structure - a kinematic model with 40 rotational degrees of freedom. To overcome the flaws of standard edge detection, we introduce a model-based anisotropic Gaussian filter. The parameters of the anisotropic Gaussian are automatically derived from the kinematic model through the prediction of the extremal contours. The theory is validated by performing full body motion capture from six synchronized video sequences at 30 fps without markers.