Towards Vision-Based Pose- and Condition-Invariant Place Recognition along Routes
Pepperell, Edward, Corke, Peter, & Milford, Michael (2014) Towards Vision-Based Pose- and Condition-Invariant Place Recognition along Routes. In Proceedings of the Australasian Conference on Robotics and Automation 2014, Australian Robotics & Automation Association ARAA, University of Melbourne, Melbourne, Australia.
Vision-based place recognition involves recognising familiar places despite changes in environmental conditions or camera viewpoint (pose). Existing training-free methods exhibit excellent invariance to either of these challenges, but not both simultaneously. In this paper, we present a technique for condition-invariant place recognition across large lateral platform pose variance for vehicles or robots travelling along routes. Our approach combines sideways facing cameras with a new multi-scale image comparison technique that generates synthetic views for input into the condition-invariant Sequence Matching Across Route Traversals (SMART) algorithm. We evaluate the system’s performance on multi-lane roads in two different environments across day-night cycles. In the extreme case of day-night place recognition across the entire width of a four-lane-plus-median-strip highway, we demonstrate performance of up to 44% recall at 100% precision, where current state-of-the-art fails.
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|Item Type:||Conference Paper|
|Divisions:||Current > Research Centres > ARC Centre of Excellence for Robotic Vision
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 [Please consult the Authors]|
|Deposited On:||05 Dec 2014 00:40|
|Last Modified:||12 Sep 2016 01:20|
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