Visual Object Detection for Mobile Road Sign Inventory View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2004

AUTHORS

Christin Seifert , Lucas Paletta , Andreas Jeitler , Evelyn Hödl , Jean-P. Andreu , Patrick Luley , Alexander Almer

ABSTRACT

For road sign inventory and maintenance, we propose to use a mobile system based on a handheld device, GPS sensor, a camera, and a standard mobile GIS software. Camera images are then analysed via object recognition algorithms which results in an automated detection, i.e., localisation and classification of the signs. We present here the localisation of points and regions of interest, the fitting of geometrical constraints to the extracted set of interest points, and the matching of content information from the visual information within the sign plate. From the preliminary operational state of the vision based road sign detection system we conclude that the selected methodology is efficient enough to achieve the requested high quality in object detection and classification. More... »

PAGES

491-495

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-28637-0_63

DOI

http://dx.doi.org/10.1007/978-3-540-28637-0_63

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1003347966


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