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This paper presents a vision-based approach with unsupervised learning for robust, accurate and stable detection of the drivable road to deal with autonomous driving in changing environments. This approach is based on a formulation of stereo with homography as a Maximum A Posteriori (MAP) problem in a Markov Random Field (MRF). Under this formulation, we develop an alternating optimization algorithm...
Road detection is one of the key issues for the implementation of intelligent vehicles. In this paper, we present a drivable road region detection method using homography estimation and efficient belief propagation. In the method, each pixel in stereo images is assigned a label by minimizing an energy function that accounts for the planar road region, which is defined by utilizing the 2D projective...
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