STOKLASA, Roman and Petr MATULA. Road Detection Using Similarity Search. In Roland Stelzer and Karim Jafarmadar. 2nd International Conference on Robotics in Education. Vienna: Neuveden, 2011, p. 95-102. ISBN 978-3-200-02273-7.
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Basic information
Original name Road Detection Using Similarity Search
Name in Czech Detekce cesty na základě podobnostního vyhledáváni
Authors STOKLASA, Roman (703 Slovakia, guarantor, belonging to the institution) and Petr MATULA (203 Czech Republic, belonging to the institution).
Edition Vienna, 2nd International Conference on Robotics in Education, p. 95-102, 8 pp. 2011.
Publisher Neuveden
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Austria
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/11:00053124
Organization unit Faculty of Informatics
ISBN 978-3-200-02273-7
Keywords (in Czech) detekce cesty; podobnostní vyhledávaní; klasifikace obrázků; autonomní robot; Robotour
Keywords in English road detection; similarity search; navigation; image classification; autonomous robot; Robotour
Tags best5
Tags International impact, Reviewed
Changed by Changed by: RNDr. Roman Stoklasa, Ph.D., učo 139873. Changed: 3/4/2013 15:29.
Abstract
This paper concerns vision-based navigation of autonomous robots. We propose a new approach for road detection based on similarity database searches. Images from the camera are divided into regular samples and for each sample the most visually similar images are retrieved from the database. The similarity between the samples and the image database is measured in a metric space using three descriptors: edge histogram, color structure and color layout, resulting in a classification of each sample into two classes: road and non-road with a confidence measure. The performance of our approach has been evaluated with respect to a manually defined ground-truth. The approach has been successfully applied to four videos consisting of more than 1180 frames. It turned out that our approach offers very precise classification results.
Abstract (in Czech)
Článek se zabývá detekci cesty.
Links
LA09016, research and development projectName: Účast ČR v European Research Consortium for Informatics and Mathematics (ERCIM) (Acronym: ERCIM)
Investor: Ministry of Education, Youth and Sports of the CR, Czech Republic membership in the European Research Consortium for Informatics and Mathematics
MUNI/A/0914/2009, interní kód MUName: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Acronym: SV-FI MAV)
Investor: Masaryk University, Category A
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