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 highdimensional 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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Steinhoff, U., Omerčević, D., Perko, R., Schiele, B., & Leonardis, A. (2007). How computer vision can help in outdoor positioning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4794 LNCS, pp. 124–141). Springer Verlag. https://doi.org/10.1007/978-3-540-76652-0_8
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