Presence: Teleoperators and Virtual Environments
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Augmented Reality Camera Tracking with Homographies
IEEE Computer Graphics and Applications
Pose Estimation for Planar Structures
IEEE Computer Graphics and Applications
Real-time tracking of image regions with changes in geometry and illumination
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Marker-less Tracking for AR: A Learning-Based Approach
ISMAR '02 Proceedings of the 1st International Symposium on Mixed and Augmented Reality
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
Markerless Augmented Reality with a Real-Time Affine Region Tracker
ISAR '01 Proceedings of the IEEE and ACM International Symposium on Augmented Reality (ISAR'01)
A Hybrid Registration Method for Outdoor Augmented Reality
ISAR '01 Proceedings of the IEEE and ACM International Symposium on Augmented Reality (ISAR'01)
Natural feature tracking for augmented reality
IEEE Transactions on Multimedia
Markerless augmented reality for robotic helicoptor applications
RobVis'08 Proceedings of the 2nd international conference on Robot vision
UBI, the guardian dragon: your virtual sidekick
ACE'12 Proceedings of the 9th international conference on Advances in Computer Entertainment
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Natural feature tracking is a popular research topic in computer vision and has been used in Augmented Reality (AR) applications. Current natural feature trackers have two major limitations in AR applications. Firstly, the natural features may be lost during the tracking process such that the annotations that are linked to these natural features will also be lost. Secondly, if the virtual objects have to be augmented on regions where there are no distinct natural features that can be tracked, the current natural feature cannot be used directly. This paper proposes a method for points tracking or transferring based on the Kanade-Lucas-Tomasi (KLT) feature tracker and the projective reconstruction technique. The points to be tracked include the lost natural features, and any points that are specified by the users. The proposed method is useful for AR applications, including scene annotation, registration, etc. Some indoor and outdoor experiments have been conducted to validate the performance of the proposed method.