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Overview of the CLEF 2009 robot vision track
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-1396-0102
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-1170-7162
2009 (English)In: CLEF2009 Working Notes: Working Notes for CLEF 2009 Workshop, co-located with the 13th European Conference on Digital Libraries (ECDL 2009), Corf├╣, Greece, September 30 - October 2, 2009 / [ed] Carol Peters, Nicola Ferro, CEUR-WS , 2009Conference paper, Published paper (Refereed)
Abstract [en]

The robot vision task has been proposed to the ImageCLEF participants for the first time in 2009. The task attracted a considerable attention, with 19 inscribed research groups, 7 groups eventually participating and a total of 27 submitted runs. The task addressed the problem of visual place recognition applied to robot topological localization. Specifically, participants were asked to classify rooms on the basis of image sequences, captured by a perspective camera mounted on a mobile robot. The sequences were acquired in an office environment, under varying illumination conditions and across a time span of almost two years. The training and validation set consisted of a subset of the IDOL2 database1. The test set consisted of sequences similar to those in the training and validation set, but acquired 20 months later and imaging also additional rooms. Participants were asked to build a system able to answer the question "where are you?" (I am in the kitchen, in the corridor, etc) when presented with a test sequence imaging rooms seen during training, or additional rooms that were not imaged in the training sequence. The system had to assign each test image to one of the rooms present in the training sequence, or indicate that the image came from a new room. We asked all participants to solve the problem separately for each test image (obligatory task). Additionally, results could also be reported for algorithms exploiting the temporal continuity of the image sequences (optional task). Of the 27 runs, 21 were submitted to the obligatory task, and 6 to the optional task. The best result in the obligatory task was obtained by the Multimedia Information Retrieval Group of the University of Glasgow, UK with an approach based on local feature matching. The best result in the optional task was obtained by the Intelligent Systems and Data Mining Group (SIMD) of the University of Castilla-La Mancha, Albacete, Spain, with an approach based on local features and a particle filter.

Place, publisher, year, edition, pages
CEUR-WS , 2009.
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 1175
Keyword [en]
Data mining, Digital libraries, Filtration, Image matching, Intelligent systems, Robot applications, Robots, Illumination conditions, Multimedia information retrieval, Perspective cameras, Place recognition, Robot localization, Temporal continuity, Topological localization, University of Glasgow, Computer vision
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-164558Scopus ID: 2-s2.0-84922032081OAI: oai:DiVA.org:kth-164558DiVA: diva2:806662
Conference
2009 Working Notes for CLEF Workshop, CLEF 2009 - Co-located with the 13th European Conference on Digital Libraries, ECDL 2009, 30 September 2009 through 2 October 2009
Note

QC 20150421

Available from: 2015-04-21 Created: 2015-04-17 Last updated: 2015-04-21Bibliographically approved

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Pronobis, AndrzejJensfelt, Patric

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