Simulating humans: computer graphics animation and control
Simulating humans: computer graphics animation and control
Real-time inverse kinematics techniques for anthropomorphic limbs
Graphical Models and Image Processing
Tracking persons in monocular image sequences
Computer Vision and Image Understanding
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Introduction to Robotics: Mechanics and Control
Introduction to Robotics: Mechanics and Control
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)
Reliable Tracking of Human Arm Dynamics by Multiple Cue Integration and Constraint Fusion
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Virtual 3D Blackboard: 3D Finger Tracking Using a Single Camera
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A Framework for Modeling the Appearance of 3D Articulated Figures
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Automated Body Modeling from Video Sequences
MPEOPLE '99 Proceedings of the IEEE International Workshop on Modelling People
Towards Model-Based Capture of a Persons Shape, Appearance and Motion
MPEOPLE '99 Proceedings of the IEEE International Workshop on Modelling People
Tracking Hybrid 2D-3D Human Models from Multiple Views
MPEOPLE '99 Proceedings of the IEEE International Workshop on Modelling People
Understanding Purposeful Human Motion
MPEOPLE '99 Proceedings of the IEEE International Workshop on Modelling People
Monocular tracking of the human arm in 3D
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Real-time 3d arm pose estimation from monocular video for enhanced HCI
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
Bootstrapping sequential monte carlo tracking
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Real-time viewpoint-invariant hand localization with cluttered backgrounds
Image and Vision Computing
Deictic gestures with a time-of-flight camera
GW'09 Proceedings of the 8th international conference on Gesture in Embodied Communication and Human-Computer Interaction
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Pose estimation of 3-D objects based on monocular computer vision is an ill-posed problem. To ease matters a model-based approach can be applied. Such an approach usually relies on iterating when matching the model and the image data. In this paper we estimate the 3-D pose of a human arm from a monocular image. To avoid the inherent problems when iterating, we apply an exhaustive matching strategy. To make this plausible, we reduce the size of the solution space through a very compact model representation of the arm and prune the solution space. The model is developed through a detailed investigation of the functionality and structure of the arm and the shoulder complex. The model consists of just two parameters and is based on the screw-axis representation together with image measurements. The pruning is achieved through kinematic constraints and it turns out that the solution space of the compact model can be pruned 97%, on average. Altogether, the compact representation and the constraints reduce the solution space significantly and, therefore, allow for an exhaustive matching procedure. The approach is tested in a model-based silhouette framework, and tests show promising results.