A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pose estimation using point and line correspondences
Real-Time Imaging
Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System
IWAR '99 Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
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
Fusing Points and Lines for High Performance Tracking
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Object-adaptive tracking for AR guidance system
VRCAI '08 Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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Model-based camera tracking is a technology that estimates a camera pose by tracking visual cues, i.e. points and edges on a known 3D scene model, in camera images. In model-based camera tracking, it has been a main challenge how to use the visual cues effectively for better performance. In this paper, we carefully analyze the dependency of the visual cues on tracking conditions (or environments) and propose a formula for integrating the visual cues cooperatively into a single framework based on the analysis. Then, we demonstrate that the analytic integration outperforms separate use of either cue and expedient integration of visual cues in arbitrary environments through experiments with synthetic camera images for which ground truth camera poses are given.