Real-time Estimation Of Drivable Image Area Based On Monocular Vision

dc.creatorNeto A.M.
dc.creatorVictorino A.C.
dc.creatorFantoni I.
dc.creatorFerreira J.V.
dc.date2013
dc.date2015-06-25T19:13:56Z
dc.date2015-11-26T15:11:44Z
dc.date2015-06-25T19:13:56Z
dc.date2015-11-26T15:11:44Z
dc.date.accessioned2018-03-28T22:21:50Z
dc.date.available2018-03-28T22:21:50Z
dc.identifier9781467327558
dc.identifierIeee Intelligent Vehicles Symposium, Proceedings. , v. , n. , p. 63 - 68, 2013.
dc.identifier
dc.identifier10.1109/IVS.2013.6629448
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84892411731&partnerID=40&md5=ac362084a08732f7f046f47704a70c88
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/88993
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/88993
dc.identifier2-s2.0-84892411731
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1258214
dc.descriptionCamera-based estimation of drivable image areas is still in evolution. These systems have been developed for improved safety and convenience, without the need to adapt itself to the environment. Machine Vision is an important tool to identify the region that includes the road in images. Road detection is the major task of autonomous vehicle guidance. In this way, this work proposes a drivable region detection algorithm that generates the region of interest from a dynamic threshold search method and from a drag process (DP). Applying the DP to estimation of drivable image areas has not been done yet, making the concept unique. Our system was has been evaluated from real data obtained by intelligent platforms and tested in different types of image texture, which include occlusion case, obstacle detection and reactive navigation. © 2013 IEEE.
dc.description
dc.description
dc.description63
dc.description68
dc.descriptionAustralian Dedicated Short Range Communication (AusDSRC),Griffith University Intelligent Control Systems Laboratory,Intelligent Transport Systems Australia
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dc.languageen
dc.publisher
dc.relationIEEE Intelligent Vehicles Symposium, Proceedings
dc.rightsfechado
dc.sourceScopus
dc.titleReal-time Estimation Of Drivable Image Area Based On Monocular Vision
dc.typeActas de congresos


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