Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
A Maximum Likelihood Framework for Determining Moving Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Determination of the Attitude of 3D Objects from a Single Perspective View
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting Parameterized Three-Dimensional Models to Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-based object pose in 25 lines of code
International Journal of Computer Vision - Special issue: image understanding research at the University of Maryland
Imposing hard constraints on deformable models through optimization in orthogonal subspaces
Computer Vision and Image Understanding - Special issue on physics-based modeling and reasoning in computer vision
Nonrigid motion analysis: articulated and elastic motion
Computer Vision and Image Understanding
Fast and Globally Convergent Pose Estimation from Video Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Nonrigid Motion and Structure from 2D Satellite Cloud Images without Correspondences
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Robot Control: The Task Function Approach
Robot Control: The Task Function Approach
Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Elastically Adaptive Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Multi-part Non-rigid Object Tracking Based on Time Model-Space Gradients
AMDO '00 Proceedings of the First International Workshop on Articulated Motion and Deformable Objects
3D Articulated Models and Multi-View Tracking with Silhouettes
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Rigid and Articulated Motion Seen with an Uncalibrated Stereo Rig
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Articulated Soft Objects for Multiview Shape and Motion Capture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Articulated Body by Dynamic Markov Network
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A real-time tracker for markerless augmented reality
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Articulated Body Motion Capture by Stochastic Search
International Journal of Computer Vision
Object-Based Visual 3D Tracking of Articulated Objects via Kinematic Sets
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
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In this article, a new approach is given for real-time visual tracking of a class of articulated non-rigid objects in 3D. The main contribution of this paper consists in symmetrically modeling the motion and velocity of an articulated object via a novel kinematic set approach. This is likened to a Lagrange-d'Alembert formulation in classical physics. The advantages of this new model over pre-existing methods include improved precision, robustness and efficiency, leading to real-time performance. Furthermore, a general class of mechanical joints can be considered and the method can track objects where previous approaches have failed due to a lack of visual information. In summary, a joint configuration is modeled by using Pfaffian velocity constraints. The configuration and location of a joint is then used to build a general Jacobian Matrix, which relates individual rigid body velocities (twists) to an underlying minimal subspace. A closed loop control law is then derived in order to minimize a set of distance errors in the image and estimate the system parameters. The tracking is locally based upon efficient distance criterion. Experimental results show prismatic, rotational and helical type links and eight general parameters. A statistical M-estimation technique is applied to improve robustness. A monocular camera system was used as a real-time sensor to verify the theory.