Visual route recognition with a handful of bits
Contribuinte(s) |
Roy, Nicholas |
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Data(s) |
2012
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Resumo |
In this paper we use a sequence-based visual localization algorithm to reveal surprising answers to the question, how much visual information is actually needed to conduct effective navigation? The algorithm actively searches for the best local image matches within a sliding window of short route segments or 'sub-routes', and matches sub-routes by searching for coherent sequences of local image matches. In contract to many existing techniques, the technique requires no pre-training or camera parameter calibration. We compare the algorithm's performance to the state-of-the-art FAB-MAP 2.0 algorithm on a 70 km benchmark dataset. Performance matches or exceeds the state of the art feature-based localization technique using images as small as 4 pixels, fields of view reduced by a factor of 250, and pixel bit depths reduced to 2 bits. We present further results demonstrating the system localizing in an office environment with near 100% precision using two 7 bit Lego light sensors, as well as using 16 and 32 pixel images from a motorbike race and a mountain rally car stage. By demonstrating how little image information is required to achieve localization along a route, we hope to stimulate future 'low fidelity' approaches to visual navigation that complement probabilistic feature-based techniques. |
Formato |
application/pdf |
Identificador | |
Publicador |
University of Sydney |
Relação |
http://eprints.qut.edu.au/51415/2/p38_Milford.pdf http://www.roboticsproceedings.org/rss08/p38.pdf Milford, Michael (2012) Visual route recognition with a handful of bits. In Roy, Nicholas (Ed.) Proceedings of Robotics Science and Systems Conference 2012, University of Sydney, Australia. |
Direitos |
Copyright 2012 (please consult the author). |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #080100 ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING #080101 Adaptive Agents and Intelligent Robotics #Localization #Route recognition #Visual navigation #Featureless |
Tipo |
Conference Paper |