TY - JOUR AU - Jose Manuel Alvarez AU - Antonio Lopez AU - Theo Gevers AU - Felipe Lumbreras ED - IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC PY - 2014// TI - Combining Priors, Appearance and Context for Road Detection T2 - TITS JO - IEEE Transactions on Intelligent Transportation Systems SP - 1168 EP - 1178 VL - 15 IS - 3 KW - Illuminant invariance KW - lane markings KW - road detection KW - road prior KW - road scene understanding KW - vanishing point KW - 3-D scene layout N2 - Detecting the free road surface ahead of a moving vehicle is an important research topic in different areas of computer vision, such as autonomous driving or car collision warning.Current vision-based road detection methods are usually based solely on low-level features. Furthermore, they generally assume structured roads, road homogeneity, and uniform lighting conditions, constraining their applicability in real-world scenarios. In this paper, road priors and contextual information are introduced for road detection. First, we propose an algorithm to estimate road priors online using geographical information, providing relevant initial information about the road location. Then, contextual cues, including horizon lines, vanishing points, lane markings, 3-D scene layout, and road geometry, are used in addition to low-level cues derived from the appearance of roads. Finally, a generative model is used to combine these cues and priors, leading to a road detection method that is, to a large degree, robust to varying imaging conditions, road types, and scenarios. SN - 1524-9050 L1 - http://refbase.cvc.uab.es/files/ALG2014.pdf UR - http://dx.doi.org/10.1109/TITS.2013.2295427 N1 - ADAS; 600.076;ISE ID - Jose Manuel Alvarez2014 ER -