Fast color/texture segmentation for outdoor robots

Morten Rufus Blas, Motilal Agrawal, Aravind Sundaresan, Kurt Konolige

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Abstract

We present a fast integrated approach for online segmentation of images for outdoor robots. A compact color and texture descriptor has been developed to describe local color and texture variations in an image. This descriptor is then used in a two-stage fast clustering framework using K-means to perform online segmentation of natural images. We present results of applying our descriptor for segmenting a synthetic image and compare it against other state-of-the-art descriptors. We also apply our segmentation algorithm to the task of detecting natural paths in outdoor images. The whole system has been demonstrated to work online alongside localization, 3D obstacle detection, and planning.
Original languageEnglish
Title of host publicationProceedings of 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherIEEE
Publication date2008
Pages4078-4085
ISBN (Print)9781424420575
DOIs
Publication statusPublished - 2008
EventInternational Conference on Intelligent Robots and Systems - Nice, France
Duration: 22 Sep 200826 Sep 2008
http://iros2008.inria.fr/

Conference

ConferenceInternational Conference on Intelligent Robots and Systems
CountryFrance
CityNice
Period22/09/200826/09/2008
Internet address

Bibliographical note

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