A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Pose Estimation from Points or Lines
IEEE Transactions on Pattern Analysis and Machine Intelligence
ARTag, a Fiducial Marker System Using Digital Techniques
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Robust Pose Estimation from a Planar Target
IEEE Transactions on Pattern Analysis and Machine Intelligence
An automatic calibration method for stereo-based 3D distributed smart camera networks
Computer Vision and Image Understanding
Multiview registration of 3D scenes by minimizing error between coordinate frames
IEEE Transactions on Pattern Analysis and Machine Intelligence
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An economical self-localization system which uses a monocular camera and a set of artificial landmarks is presented herein. The system represents the surrounding environment as a topological graph where each node corresponds to an artificial landmark and each edge corresponds to a relative pose between two landmarks. The edges are weighted based on an error metric (related to pose uncertainty) and a shortest path algorithm is applied to the map to compute the path corresponding to the least aggregate weight. This path is used to localize the camera with respect to a global coordinate system whose origin lies on an arbitrary reference landmark (i.e., the destination node of the path). The proposed system does not require a preliminary training process, as it builds and updates the map online. Experimental results demonstrate the performance of the system in reducing the global error associated with large-scale localization.