FAB-MAP: Probabilistic localization and mapping in the space of appearance. Cummins, M. & Newman, P. International Journal of Robotics Research, 27(6):647-665, 2008.
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This paper describes a probabilistic approach to the problem of recognizing places based on their appearance. The system we present is not limited to localization, but can determine that a new observation comes from a previously unseen place, and so augment its map. Effectively this is a SLAM system in the space of appearance. Our probabilistic approach allows us to explicitly account for perceptual aliasing in the environment-identical but indistinctive observations receive a low probability of having come from the same place. We achieve this by learning a generative model of place appearance. By partitioning the learning problem into two parts, new place models can be learned online from only a single observation of a place. The algorithm complexity is linear in the number of places in the map, and is particularly suitable for online loop closure detection in mobile robotics. © 2008 SAGE Publications.
@article{
 title = {FAB-MAP: Probabilistic localization and mapping in the space of appearance},
 type = {article},
 year = {2008},
 keywords = {Appearance based navigation,Place recognition,Topological SLAM},
 pages = {647-665},
 volume = {27},
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 abstract = {This paper describes a probabilistic approach to the problem of recognizing places based on their appearance. The system we present is not limited to localization, but can determine that a new observation comes from a previously unseen place, and so augment its map. Effectively this is a SLAM system in the space of appearance. Our probabilistic approach allows us to explicitly account for perceptual aliasing in the environment-identical but indistinctive observations receive a low probability of having come from the same place. We achieve this by learning a generative model of place appearance. By partitioning the learning problem into two parts, new place models can be learned online from only a single observation of a place. The algorithm complexity is linear in the number of places in the map, and is particularly suitable for online loop closure detection in mobile robotics. © 2008 SAGE Publications.},
 bibtype = {article},
 author = {Cummins, Mark and Newman, Paul},
 doi = {10.1177/0278364908090961},
 journal = {International Journal of Robotics Research},
 number = {6}
}

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