Multi-scale bio-inspired place recognition
Chen, Zetao, Jacobson, Adam, Erdem, Uğur M., Hasselmo, Michael E., & Milford, Michael (2014) Multi-scale bio-inspired place recognition. In Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA 2014), IEEE, Hong Kong Convention and Exhibition Center, Hong Kong, China, pp. 1895-1901.
This paper presents a novel place recognition algorithm inspired by the recent discovery of overlapping and multi-scale spatial maps in the rodent brain. We mimic this hierarchical framework by training arrays of Support Vector Machines to recognize places at multiple spatial scales. Place match hypotheses are then cross-validated across all spatial scales, a process which combines the spatial specificity of the finest spatial map with the consensus provided by broader mapping scales. Experiments on three real-world datasets including a large robotics benchmark demonstrate that mapping over multiple scales uniformly improves place recognition performance over a single scale approach without sacrificing localization accuracy. We present analysis that illustrates how matching over multiple scales leads to better place recognition performance and discuss several promising areas for future investigation.
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|Item Type:||Conference Paper|
|Keywords:||Robotics, Multi-scale place recognition, Support Vector Machines, Localization accuracy, Robotic mapping|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2014 Please consult the authors|
|Deposited On:||24 Jul 2014 22:24|
|Last Modified:||19 Sep 2016 06:04|
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