All-environment visual place recognition with SMART

Pepperell, Edward, Corke, Peter, & Milford, Michael (2014) All-environment visual place recognition with SMART. In Proceedings of the International Conference on Robotics and Automation, IEEE, Hong Kong Convention and Exhibition Center, Hong Kong, pp. 1612-1618.

View at publisher (open access)


This paper presents Sequence Matching Across Route Traversals (SMART); a generally applicable sequence-based place recognition algorithm. SMART provides invariance to changes in illumination and vehicle speed while also providing moderate pose invariance and robustness to environmental aliasing. We evaluate SMART on vehicles travelling at highly variable speeds in two challenging environments; firstly, on an all-terrain vehicle in an off-road, forest track and secondly, using a passenger car traversing an urban environment across day and night. We provide comparative results to the current state-of-the-art SeqSLAM algorithm and investigate the effects of altering SMART’s image matching parameters. Additionally, we conduct an extensive study of the relationship between image sequence length and SMART’s matching performance. Our results show viable place recognition performance in both environments with short 10-metre sequences, and up to 96% recall at 100% precision across extreme day-night cycles when longer image sequences are used.

Impact and interest:

21 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

187 since deposited on 11 Jun 2014
45 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 72732
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Robot Vision, Place Recognition, Localisation
DOI: 10.1109/ICRA.2014.6907067
ISBN: 978-1-4799-3685-4
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 IEEE
Deposited On: 11 Jun 2014 22:36
Last Modified: 12 Sep 2016 15:34

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page