Clustering Algorithm Exploring Road Geometry in a Video-Based Driver Assistant System
In this paper we present two algorithms for an advanced driver assistance system to investigate road geometry. The proposed solutions can handle both simple and complex scenarios, e.g. construction zones. Our input data consists of segments and polygonal paths, whose clustering gives a proper input for a lane model. The presented methods use thresholding and spectral clustering approaches.
This research was supported by the project EFOP-3.6.2-16-2017-00015.
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