Robust model-based motion tracking through the integration of search and estimation
International Journal of Computer Vision
Robust methods for estimating pose and a sensitivity analysis
CVGIP: Image Understanding
Object pose from 2-D to 3-D point and line correspondences
International Journal of Computer Vision
Pose estimation using point and line correspondences
Real-Time Imaging
Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Smoothing Filter for CONDENSATION
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
3D Model Based Pose Determination in Real-Time: Strategies, Convergence, Accuracy
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
A real-time tracker for markerless augmented reality
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
A Robust Hybrid Tracking System for Outdoor Augmented Reality
VR '04 Proceedings of the IEEE Virtual Reality 2004
Combining Edge and Texture Information for Real-Time Accurate 3D Camera Tracking
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Online camera pose estimation in partially known and dynamic scenes
ISMAR '06 Proceedings of the 5th IEEE and ACM International Symposium on Mixed and Augmented Reality
Going out: robust model-based tracking for outdoor augmented reality
ISMAR '06 Proceedings of the 5th IEEE and ACM International Symposium on Mixed and Augmented Reality
Automatic contour model creation out of polygonal CAD models for markerless Augmented Reality
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
A Fast Initialization Method for Edge-based Registration Using an Inclination Constraint
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
IEICE - Transactions on Information and Systems
ICCVG 2008 Proceedings of the International Conference on Computer Vision and Graphics: Revised Papers
Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Pose tracking from natural features on mobile phones
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Complemental Use of Multiple Cameras for Stable Tracking of Multiple Markers
VMR '09 Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009
Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology
Robust camera egomotion estimation from 3D straight line-based environment model
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Adaptable model-based tracking using analysis-by-synthesis techniques
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
An experimental augmented reality platform for assisted maritime navigation
Proceedings of the 1st Augmented Human International Conference
MobileAR Browser - A generic architecture for rapid AR-multi-level development
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
We present a real-time model-based line tracking approach with adaptive learning of image edge features that can handle partial occlusion and illumination changes. A CAD (VRML) model of the object to track is needed. First, the visible edges of the model with respect to the camera pose estimate are sorted out by a visibility test performed on standard graphics hardware. For every sample point of every projected visible 3D model line a search for gradient maxima in the image is then carried out in a direction perpendicular to that line. Multiple hypotheses of these maxima are considered as putative matches. The camera pose is updated by minimizing the distances between the projection of all sample points of the visible 3D model lines and the most likely matches found in the image. The state of every edge's visual properties is updated after each successful camera pose estimation.We evaluated the algorithm and showed the improvements compared to other tracking approaches.