Scalable place recognition under appearance change for autonomous driving

Anh-Dzung Doan, Yasir Latif, Tat-Jun Chin, Yu Liu, Thanh-Toan Do, Ian Reid

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

8 Citations (Scopus)

Abstract

A major challenge in place recognition for autonomous driving is to be robust against appearance changes due to short-term (e.g., weather, lighting) and long-term (seasons, vegetation growth, etc.) environmental variations. A promising solution is to continuously accumulate images to maintain an adequate sample of the conditions and incorporate new changes into the place recognition decision. However, this demands a place recognition technique that is scalable on an ever growing dataset. To this end, we propose a novel place recognition technique that can be efficiently retrained and compressed, such that the recognition of new queries can exploit all available data (including recent changes) without suffering from visible growth in computational cost. Underpinning our method is a novel temporal image matching technique based on Hidden Markov Models. Our experiments show that, compared to state-of-the-art techniques, our method has much greater potential for large-scale place recognition for autonomous driving.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Computer Vision, ICCV 2019
EditorsIn So Kweon, Nikos Paragios, Ming-Hsuan Yang, Svetlana Lazebnik
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages9318-9327
Number of pages10
ISBN (Electronic)9781728148038
ISBN (Print)9781728148045
DOIs
Publication statusPublished - 2019
Externally publishedYes
EventIEEE International Conference on Computer Vision 2019 - Seoul, Korea, Republic of (South)
Duration: 27 Oct 20192 Nov 2019
Conference number: 17th
http://iccv2019.thecvf.com/
https://ieeexplore.ieee.org/xpl/conhome/8972782/proceeding (Proceedings)

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
PublisherThe Institute of Electrical and Electronics Engineers, Inc.
Volume2019-October
ISSN (Print)1550-5499
ISSN (Electronic)2380-7504

Conference

ConferenceIEEE International Conference on Computer Vision 2019
Abbreviated titleICCV 2019
CountryKorea, Republic of (South)
CitySeoul
Period27/10/192/11/19
Internet address

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