A Maximum Likelihood Framework for Determining Moving Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting Parameterized Three-Dimensional Models to Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust methods for estimating pose and a sensitivity analysis
CVGIP: Image Understanding
Fast and Globally Convergent Pose Estimation from Video Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Stable Real-Time 3D Tracking Using Online and Offline Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Adaptive Line Tracking with Multiple Hypotheses for Augmented Reality
ISMAR '05 Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality
Real-time Hybrid Tracking using Edge and Texture Information
International Journal of Robotics Research
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This paper presents a new robust and reliable marker less camera tracking system for outdoor augmented reality using only a mobile handheld camera. The proposed method is particularly efficient for partially known 3D scenes where only an incomplete 3D model of the outdoor environment is available. Indeed, the system combines an edge-based tracker with a sparse 3D reconstruction of the real-world environment to continually perform the camera tracking even if the model-based tracker fails. Experiments on real data were carried out and demonstrate the robustness of our approach to occlusions and scene changes.