Multiple Lane Detection Algorithm Based on Novel Dense Vanishing Point Estimation
The detection of multiple curved lane markings is still a challenge for advanced driver assistance systems today, due to interference such as road markings and shadows cast by roadside structures and vehicles. The vanishing point V p contains the global information of the road image. Hence, V p -bas...
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Published in | IEEE transactions on intelligent transportation systems Vol. 18; no. 3; pp. 621 - 632 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
IEEE
01.03.2017
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Subjects | |
Online Access | Get full text |
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Summary: | The detection of multiple curved lane markings is still a challenge for advanced driver assistance systems today, due to interference such as road markings and shadows cast by roadside structures and vehicles. The vanishing point V p contains the global information of the road image. Hence, V p -based lane detection algorithms are quite insensitive to interference. When curved lanes are assumed, V p shifts with respect to the rows of the image. In this paper, a V p for each individual row of the image is estimated by first extracting a V py (vertical position of the V p ) for each individual row of the image from the v-disparity. Then, based on the estimated V py 's, a 2-D V px (horizontal position of the V p ) accumulator is efficiently formed. Thus, by globally optimizing this 2-D V px accumulator, globally optimum V p s for the road image are extracted. Then, estimated V p s are utilized for multiple curved lane marking detection on nonflat road surfaces. The resultant system achieves a detection rate of 99% in 1862 frames of six stereo vision test sequences. |
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ISSN: | 1524-9050 1558-0016 |
DOI: | 10.1109/TITS.2016.2586187 |