Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape quantization and recognition with randomized trees
Neural Computation
Computer Vision and Image Understanding
Real-Time Localisation and Mapping with Wearable Active Vision
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Stable Real-Time 3D Tracking Using Online and Offline Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scene Modelling, Recognition and Tracking with Invariant Image Features
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
Online Estimation of Trifocal Tensors for Augmenting Live Video
ISMAR '04 Proceedings of the 3rd IEEE/ACM International Symposium on Mixed and Augmented Reality
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
OpenVIDIA: parallel GPU computer vision
Proceedings of the 13th annual ACM international conference on Multimedia
Registration Using Natural Features for Augmented Reality Systems
IEEE Transactions on Visualization and Computer Graphics
Keypoint Recognition Using Randomized Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
MonoSLAM: Real-Time Single Camera SLAM
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving the Agility of Keyframe-Based SLAM
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Parallel Tracking and Mapping for Small AR Workspaces
ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
Multithreaded Hybrid Feature Tracking for Markerless Augmented Reality
IEEE Transactions on Visualization and Computer Graphics
Natural feature tracking for augmented reality
IEEE Transactions on Multimedia
A Vision-Based Augmented-Reality System For Multiuser Collaborative Environments
IEEE Transactions on Multimedia
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This research focuses on designing a robust and flexible registration method for wide-area augmented reality applications using scene recognition and natural features tracking techniques. Instead of building a global map of the wide-area scene, we propose to partition the whole scene into several sub-maps according to the user's preference or the requirements of the augmented reality (AR) applications. Random classification trees are used to learn and recognize the reconstructed scenes because they naturally handle multi-class problems, while being both robust and fast. The result is a system that can deal with large scale scene that previous methods cannot cope with. We also propose a hybrid natural features tracking strategy combining both wide and narrow baseline techniques. While providing seamless registration, our system can recover from registration failures and switch between different sub-maps automatically. Experimental results demonstrate the validity of the proposed method for wide-area augmented reality applications.