Incremental learning for place recognition in dynamic environments
2007 (English)In: Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on, IEEE , 2007, 721-728 p.Conference paper (Refereed)
Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, visual recognition algorithms should be adaptive, i.e. should be able to learn from experience and adapt continuously to changes in the environment. This paper presents a discriminative incremental learning approach to place recognition. We use a recently introduced version of the incremental SVM, which allows to control the memory requirements as the system updates its internal representation. At the same time, it preserves the recognition performance of the batch algorithm. In order to assess the method, we acquired a database capturing the intrinsic variability of places over time. Extensive experiments show the power and the potential of the approach.
Place, publisher, year, edition, pages
IEEE , 2007. 721-728 p.
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-61518DOI: 10.1109/IROS.2007.4398986ISI: 000254073200114ScopusID: 2-s2.0-51349116583ISBN: 978-1-4244-0912-9OAI: oai:DiVA.org:kth-61518DiVA: diva2:479306
2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007; San Diego, CA; 29 October 2007 through 2 November 2007
QC 201202192012-01-172012-01-172012-02-19Bibliographically approved