S. Se, D. Lowe, and J. Little. Global localization using distinctive visual features. In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pages 226--231, Lausanne, Switzerland, October 2002. Home/Search Document Details and Download
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Comparing Image-Based Localization Methods - Robert Sim And (2003) (2 citations) (Correct)
....with recognizing familiar locations. It has been approached as both a coarse place recognition problem (e.g. based on color histograms for familiar locations [Ulrich and Nourbakhsh, 2000] and also as a problem of recognizing a set of local features associated with a specific location (for example [Se et al. 2002] ) In several approaches, authors have suggested interpolating between familiar locations to produce a position estimate more accurate than the density of training data, using either global image features ( Nayar et al. 1994; Pourraz and Crowley, 1999] or sets of local image features ( Sim and ....
S. Se, D. Lowe, and J. Little. Global localization using distinctive visual features. In Proc. Int. Conf on Intelligent Robots and Systems (IROS), pages 226--231, Lausanne, Switzerland, October 2002.
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S. Se, D. Lowe, and J. Little. Global localization using distinctive visual features. In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pages 226--231, Lausanne, Switzerland, October 2002.
Metric Localization with Scale-Invariant Visual.. - Bennewitz.. (Correct)
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S. Se, D.G. Lowe, and J.J. Little. Global localization using distinctive visual features. In Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2002.
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