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https://hdl.handle.net/2440/124483
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Type: | Conference paper |
Title: | Addressing challenging place recognition tasks using generative adversarial networks |
Author: | Latif, Y. Garg, R. Milford, M. Reid, I. |
Citation: | IEEE International Conference on Robotics and Automation, 2018, pp.2349-2355 |
Publisher: | IEEE |
Publisher Place: | Piscataway, NJ. |
Issue Date: | 2018 |
Series/Report no.: | IEEE International Conference on Robotics and Automation ICRA |
ISBN: | 1538630818 9781538630815 |
ISSN: | 1050-4729 2577-087X |
Conference Name: | IEEE International Conference on Robotics and Automation (ICRA) (21 May 2018 - 25 May 2018 : Brisbane, Australia) |
Statement of Responsibility: | Yasir Latif, Ravi Garg, Michael Milford and Ian Reid |
Abstract: | Place recognition is an essential component of Simultaneous Localization And Mapping (SLAM). Under severe appearance change, reliable place recognition is a difficult perception task since the same place is perceptually very different in the morning, at night, or over different seasons. This work addresses place recognition as a domain translation task. Using a pair of coupled Generative Adversarial Networks (GANs), we show that it is possible to generate the appearance of one domain (such as summer) from another (such as winter) without requiring image-to-image correspondences across the domains. Mapping between domains is learned from sets of images in each domain without knowing the instanceto- instance correspondence by enforcing a cyclic consistency constraint. In the process, meaningful feature spaces are learned for each domain, the distances in which can be used for the task of place recognition. Experiments show that learned features correspond to visual similarity and can be effectively used for place recognition across seasons. |
Rights: | ©2018 IEEE |
DOI: | 10.1109/ICRA.2018.8461081 |
Grant ID: | http://purl.org/au-research/grants/arc/CE140100016 http://purl.org/au-research/grants/arc/FL130100102 |
Published version: | https://ieeexplore.ieee.org/xpl/conhome/8449910/proceeding |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
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