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@TECHREPORT{Ullah_Idiap-RR-40-2010,
         author = {Ullah, Muhammad Muneeb and Pronobis, Andrzej and Caputo, Barbara and Luo, Jie and Jensfelt, Patric and Christensen, Henrik I.},
       projects = {Idiap, DIRAC},
          month = {11},
          title = {Towards Robust Place Recognition for Robot Localization},
           type = {Idiap-RR},
         number = {Idiap-RR-40-2010},
           year = {2010},
    institution = {Idiap},
       abstract = {Localization and context interpretation are two
key competences for mobile robot systems. Visual place recognition,
as opposed to purely geometrical models, holds promise of
higher flexibility and association of semantics to the model. Ideally,
a place recognition algorithm should be robust to dynamic
changes and it should perform consistently when recognizing
a room (for instance a corridor) in different geographical
locations. Also, it should be able to categorize places, a crucial
capability for transfer of knowledge and continuous learning.
In order to test the suitability of visual recognition algorithms
for these tasks, this paper presents a new database, acquired in
three different labs across Europe. It contains image sequences
of several rooms under dynamic changes, acquired at the same
time with a perspective and omnidirectional camera, mounted
on a socket. We assess this new database with an appearance
based algorithm that combines local features with support
vector machines through an ad-hoc kernel. Results show the
effectiveness of the approach and the value of the database},
            pdf = {https://publications.idiap.ch/attachments/reports/2008/Ullah_Idiap-RR-40-2010.pdf}
}