SCAAT: incremental tracking with incomplete information
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
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IEEE Computer Graphics and Applications
ISWC '01 Proceedings of the 5th IEEE International Symposium on Wearable Computers
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
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IEEE Computer Graphics and Applications
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ISMAR '06 Proceedings of the 5th IEEE and ACM International Symposium on Mixed and Augmented Reality
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SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
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The Visual Computer: International Journal of Computer Graphics
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Outdoor augmented reality systems often rely on GPS to cover large environments. Visual tracking approaches can provide more accurate location estimates but typically require a manual initialisation procedure. This paper describes the combination of both techniques to create an accurate localisation system that does not require any additional input for (re-)initialisation. The 2D GPS position together with average user height is used as an initial estimate for the visual tracking. The large gap in available GPS accuracy versus required accuracy for initialisation is overcome through a search procedure that tries to minimise search time by improving the likelihood of finding the correct estimate early. Re-initialisation of the visual tracking system after catastrophic failures is further improved by modelling the GPS error with a Gaussian process to provide a better estimate of the current location, thereby decreasing search time.