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Support Vector Machines For Understanding Lane Color and Sidewalks

Authors: Hoon Lee, Soonyoung Park, Kyoungho Choi


Understanding road features such as lanes, the color of lanes, and sidewalks in a live video captured from a moving vehicle is essential to build video-based navigation systems. In this paper, we present a novel idea to understand the road features using support vector machines. Various feature vectors including color components of road markings and the difference between two regions, i.e., chosen AOIs, and so on are fed into SVM, deciding colors of lanes and sidewalks robustly. Experimental results are provided to show the robustness of the proposed idea.

Keywords: autonomous vehicles, Lane Detection, video-based navigation system, SVMs

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