Parallel Tracking and Mapping for Small AR Workspaces


This paper presents a method of estimating camera pose in an unknown scene. While this has previously been attempted by adapting SLAM algorithms developed for robotic exploration, we propose a system specifically designed to track a hand-held camera in a small AR workspace. We propose to split tracking and mapping into two separate tasks, processed in parallel threads on a dual-core computer: one thread deals with the task of robustly tracking erratic hand-held motion, while the other produces a 3D map of point features from previously observed video frames. This allows the use of computationally expensive batch optimisation techniques not usually associated with real-time operation: The result is a system that produces detailed maps with thousands of landmarks which can be tracked at frame-rate, with an accuracy and robustness rivalling that of state-of-the-art model-based systems.

DOI: 10.1109/ISMAR.2007.4538852

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@inproceedings{Klein2007ParallelTA, title={Parallel Tracking and Mapping for Small AR Workspaces}, author={Georg Klein and David W. Murray}, booktitle={ISMAR}, year={2007} }