Depth Estimation of Urban Road Image Based on Contour Understanding

Weili, 丁伟利 Ding; Yong, 李勇 Li; Wenfeng, 王文锋 Wang; Xiuyan, 曹秀燕 Cao

doi:10.3788/aos201434.0715001

Cited by 5 publications

(3 citation statements)

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“…According to the straight line detection algorithm, if the main direction angle of any line segment l i satisfies θ i ∈ [90 − σ,9 0+σ], (0 < i ≤ m), we define the line l i as a vertical line. We set σ ∈ [5,10] because the error in vertical lines is generally not large in road images.…”

Section: Region Segmentation Based On the Envelope Of The Vertical Linesmentioning

confidence: 99%

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Efficient vanishing point detection method in complex urban road environments

Ding

2015

IET Computer Vision

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Detecting the vanishing point in a road image is important for robot navigation, intelligent transportation and other fields. This study proposes a new vanishing point detection method that uses the vertical information in complex urban road and street environments. First, all straight lines in the road image are detected based on curvature scale space and principal component analysis methods. Second, a new road region extraction method is proposed to support vanishing point detection. In this method, the image is decomposed into approximate sky, vertical and road regions using the estimation envelopes of the vertical lines. Third, the straight lines in the road region are extracted using a path perspective triangle and line length limits. The straight lines are then categorised into groups using proposed grouping strategies. Finally, vanishing point candidates are calculated from paired lines extracted from different groups and from the same group, and the final vanishing point is then estimated for the urban road scene using the mean shift clustering method. The experimental results show that the proposed algorithm can estimate the vanishing point accurately and efficiently in complex urban road environments, despite interference from vehicles and pedestrians and on curved and unstructured roads.

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Section: Region Segmentation Based On the Envelope Of The Vertical Linesmentioning

confidence: 99%

“…Vanishing points are the most useful features in road images [1][2][3], and they are widely used in fields such as autonomous driving, robot navigation, intelligent transportation and three-dimensional reconstruction [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Efficient vanishing point detection method in complex urban road environments

Ding

2015

IET Computer Vision

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“…Detecting vanishing point in a road image is important for depth estimation [1], camera calibration [2], three‐dimensional (3D) reconstruction [3], autonomous driving [4], robot navigation [5] and so on.…”

Section: Introductionmentioning

confidence: 99%

Efficient vanishing point detection method in unstructured road environments based on dark channel prior

Ding

Liu

2016

IET Computer Vision

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Vanishing point detection is a key technique in the fields such as road detection, camera calibration and visual navigation. This study presents a new vanishing point detection method, which delivers efficiency by using a dark channel prior‐based segmentation method and an adaptive straight lines search mechanism in the road region. First, the dark channel prior information is used to segment the image into a series of regions. Then the straight lines are extracted from the region contours, and the straight lines in the road region are estimated by a vertical envelope and a perspective quadrilateral constraint. The vertical envelope roughly divides the whole image into sky region, vertical region and road region. The perspective quadrilateral constraint, as the authors defined herein, eliminates the vertical lines interference inside the road region to extract the approximate straight lines in the road region. Finally, the vanishing point is estimated by the meanshift clustering method, which are computed based on the proposed grouping strategies and the intersection principles. Experiments have been conducted with a large number of road images under different environmental conditions, and the results demonstrate that the authors’ proposed algorithm can estimate vanishing point accurately and efficiently in unstructured road scenes.

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