Computer Vision System with 2D and 3D Data Fusion for Detection of Possible Auxiliaries Routes in Stretches of Interdicted Roads

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dc.contributor.author Bruno, Diego
dc.contributor.author Peres Nunes Matias, Lucas
dc.contributor.author Amaro, Jean
dc.contributor.author Osório, Fernando Santos
dc.contributor.author Wolf, Denis
dc.date.accessioned 2019-01-03T01:00:07Z
dc.date.available 2019-01-03T01:00:07Z
dc.date.issued 2019-01-08
dc.description.abstract In this paper we present an intelligent system to help autonomous vehicles in real cities and with local traffic rules. A 2D and 3D visual attention system is proposed, capable of detecting the use of signs and aids in cases of major roadblock (road under work, with a traffic accident, etc.). For this to be possible, we analyze the cones and traffic signs that usually alert a driver about this type of problem. The main objective is to provide support for autonomous vehicles to be able to find an auxiliary route that is not previously mapped. For this we use a Grid Point Cloud Map. Using the ORB-SLAM visual odometry system we can correctly fit each stereo frame point cloud in the pose where the images were collected. With the concatenation of point clouds generated by the stereo camera, every grid block can draw the main characteristics of its region and an auxiliary route can be mapped. In this type of situation the vision system must work in real time. The results are promising and very satisfactory, we obtained an accuracy of 98.4% in the 2D classification task and 83% accuracy in the single frame 3D detection task.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2019.887
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/60174
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Smart (City) Application Development: Challenges and Experiences
dc.subject Software Technology
dc.subject Computer Vision, Deep Learning, Path Planning, Stereo Vision, Traffic-Sign Detection
dc.title Computer Vision System with 2D and 3D Data Fusion for Detection of Possible Auxiliaries Routes in Stretches of Interdicted Roads
dc.type Conference Paper
dc.type.dcmi Text
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