A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Visual Tracking of Complex Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
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
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Machine learning for high-speed corner detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Feature harvesting for tracking-by-detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
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
OutlinAR: an assisted interactive model building system with reduced computational effort
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
In-Situ 3D Indoor Modeler with a Camera and Self-contained Sensors
VMR '09 Proceedings of the 3rd International Conference on Virtual and Mixed Reality: Held as Part of HCI International 2009
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Many of the robust visual tracking techniques utilized by augmented reality applications rely on 3D models and information extracted from images. Models enhanced with image information make it possible to initialize tracking and detect poor registration. Unfortunately, generating 3D CAD models and registering them to image information can be a time consuming operation. Regularly the process requires multiple trips between the site being modeled and the workstation used to create the model. The system presented in this work eliminates the need for a separately generated 3D model by utilizing modern structure-from-motion techniques to extract the model and associated image information directly from an image sequence. The technique can be implemented on any handheld device instrumented with a camera and network connection. The process of creating the model requires minimal user interaction in the form of a few cues to identify planar regions on the object of interest. In addition the system selects a set of keyframes for each region to capture viewpoint based appearance changes. This work also presents a robust tracking framework to take advantage of these new edge models. Performance of both the modeling technique and the tracking system are verified on several different objects.