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
Object pose from 2-D to 3-D point and line correspondences
International Journal of Computer Vision
Linear N-Point Camera Pose Determination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual servoing-based augmented reality
IWAR '98 Proceedings of the international workshop on Augmented reality : placing artificial objects in real scenes: placing artificial objects in real scenes
Robust Parameter Estimation in Computer Vision
SIAM Review
A Theory of Single-Viewpoint Catadioptric Image Formation
International Journal of Computer Vision
Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Pose Estimation from Points or Lines
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
A Unifying Theory for Central Panoramic Systems and Practical Applications
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Pose Estimation for Central Catadioptric Systems: An Analytical Approach
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Analysis and Solutions of the Three Point Perspective Pose Estimation Problem
Analysis and Solutions of the Three Point Perspective Pose Estimation Problem
Geometry and Convergence Analysis of Algorithms for Registration of 3D Shapes
International Journal of Computer Vision
Real-Time Markerless Tracking for Augmented Reality: The Virtual Visual Servoing Framework
IEEE Transactions on Visualization and Computer Graphics
Stochastic Local Search for Omnidirectional Catadioptric Stereovision Design
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
EPnP: An Accurate O(n) Solution to the PnP Problem
International Journal of Computer Vision
Global Optimization through Rotation Space Search
International Journal of Computer Vision
3D model based pose estimation for omnidirectional stereovision
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Conic fitting using the geometric distance
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Optimal non-iterative pose estimation via convex relaxation
Image and Vision Computing
Model-Based Multiple Rigid Object Detection and Registration in Unstructured Range Data
International Journal of Computer Vision
Statistically robust 2-D visual servoing
IEEE Transactions on Robotics
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The current work addresses the problem of 3D model tracking in the context of monocular and stereo omnidirectional vision in order to estimate the camera pose. To this end, we track 3D objects modeled by line segments because the straight line feature is often used to model the environment. Indeed, we are interested in mobile robot navigation using omnidirectional vision in structured environments. In the case of omnidirectional vision, 3D straight lines are projected as conics in omnidirectional images. Under certain conditions, these conics may have singularities. In this paper, we present two contributions. We, first, propose a new spherical formulation of the pose estimation withdrawing singularities, using an object model composed of lines. The theoretical formulation and the validation on synthetic images thus show that the new formulation clearly outperforms the former image plane one. The second contribution is the extension of the spherical representation to the stereovision case. We consider in the paper a sensor which combines a camera and four mirrors. Results in various situations show the robustness to illumination changes and local mistracking. As a final result, the proposed new stereo spherical formulation allows us to localize online a robot indoor and outdoor whereas the classical formulation fails.