Efficient Vanishing Point Detection for Driving Assistance Based on Visual Saliency Map and Image Segmentation from a Vehicle Black-Box Camera

Abstract

Techniques for detecting a vanishing point (VP) which estimates the direction of a vehicle by analyzing its relationship with surrounding objects have gained considerable attention recently. VPs can be used to support safe vehicle driving in areas such as for autonomous driving, lane-departure avoidance, distance estimation, and road-area detection, by detecting points in which parallel extension lines of objects are concentrated at a single point in a 3D space. In this paper, we proposed a method of detecting the VP in real time for applications to intelligent safe-driving support systems. In order to support safe driving of autonomous vehicles, it is necessary to drive the vehicle with the VP in center of the road image in order to prevent the vehicle from moving out of the road area while driving. Accordingly, in order to detect the VP in the road image, a method of detecting a point where straight lines intersect in an area where edge directional feature information is concentrated is required. The visual attention model and image segmentation process are applied to quickly identify candidate VPs in the area where the edge directional feature-information is concentrated and the intensity contrast difference is large. In the proposed method, VPs are detected by analyzing the edges, visual-attention regions, linear components using the Hough transform, and image segmentation results in an input image. Our experimental results have shown that the proposed method could be applied to safe-driving support systems.

Improvement of Deep Learning-based Human Detection using Dynamic Thresholding for Intelligent Surveillance System

“…To solve this problem, we may improve the selection of dynamic threshold by considering the distance between the candidate object and the vanishing point. In this case, we should integrate the vanishing point detection [17] [18]. Another solution is by utilizing the super-resolution method for very far objects [19].…”

A Coarse-to-Fine Framework for Multiple Pedestrian Crossing Detection

“…Vanishing point detection is an important technique in the fields such as road detection, camera calibration and visual navigation [19][20][21][22][23]. Vanishing point be estimated using the symmetrical features of the surrounding structure in the image [19].…”

“…Vanishing point detection is an important technique in the fields such as road detection, camera calibration and visual navigation [19][20][21][22][23]. Vanishing point be estimated using the symmetrical features of the surrounding structure in the image [19]. Two methods are commonly used to search the vanishing points: The first one searches for vanishing points based on Hough transform [19,20,24].…”

“…Vanishing point be estimated using the symmetrical features of the surrounding structure in the image [19]. Two methods are commonly used to search the vanishing points: The first one searches for vanishing points based on Hough transform [19,20,24]. In this approach, after obtaining line features using Hough transform, the vanishing point will be the point at which the majority of the supporting line segment primitives intersect.…”

A Robust Road Vanishing Point Detection Adapted to the Real-world Driving Scenes

“…Recently, the number of geometrical feature-based methods for R-VP detection increased significantly. These recent existing methods can be classified into four groups based on types of geometrical features used in the methods, such as line segment-based [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ], edge-based [ 30 , 31 , 32 , 33 ], motion-based [ 34 , 35 , 36 , 37 ], and texture-based methods [ 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 ].…”