Abstract
Localization technologies have been an important focus in ubiquitous computing. This paper explores an underrepresented area, namely computer vision technology, for outdoor positioning. More specifically we explore two modes of positioning in a challenging real world scenario: single snapshot based positioning, improved by a novel high-dimensional feature matching method, and continuous positioning enabled by combination of snapshot and incremental positioning. Quite interestingly, vision enables localization accuracies comparable to GPS. Furthermore the paper also analyzes and compares possibilities offered by the combination of different subsets of positioning technologies such as WiFi, GPS and dead reckoning in the same real world scenario as for vision based positioning.
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Steinhoff, U., Omerčević, D., Perko, R., Schiele, B., Leonardis, A. (2007). How Computer Vision Can Help in Outdoor Positioning. In: Schiele, B., et al. Ambient Intelligence. AmI 2007. Lecture Notes in Computer Science, vol 4794. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76652-0_8
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DOI: https://doi.org/10.1007/978-3-540-76652-0_8
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