Abstract
This paper presents a new approach to the integration of different sensory cues in bubble space for place recognition. In bubble space, bubble surfaces enable the representation of all features in a manner that is implicitly dependent on robot pose while preserving their local S 2-geometry. In the proposed approach, for each place, distinct groups of bubble surfaces conduce different cue descriptors which are then combined together. Unlike most previous work, merging cues of different nature is very simple regardless of the number of observations associated with each cue. Comparative experiments on a benchmark dataset indicate that while learning times are decreased considerably, recognition rates are comparable to state-of-the art approaches in place recognition.
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Erkent, Ö., Bozma, I. (2013). Integrating Cue Descriptors in Bubble Space for Place Recognition. In: Chen, M., Leibe, B., Neumann, B. (eds) Computer Vision Systems. ICVS 2013. Lecture Notes in Computer Science, vol 7963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39402-7_32
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DOI: https://doi.org/10.1007/978-3-642-39402-7_32
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