Road Detection Using Similarity Search

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F11%3A00053124" target="_blank" >RIV/00216224:14330/11:00053124 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Road Detection Using Similarity Search

Popis výsledku v původním jazyce

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 twoclasses: 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.

Název v anglickém jazyce

Road Detection Using Similarity Search

Popis výsledku anglicky

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 twoclasses: 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.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/LA09016" target="_blank" >LA09016: Účast ČR v European Research Consortium for Informatics and Mathematics (ERCIM)</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2nd International Conference on Robotics in Education

ISBN

978-3-200-02273-7

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

95-102

Název nakladatele

Neuveden

Místo vydání

Vienna

Místo konání akce

Vienna, Austria

Datum konání akce

15. 9. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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