Road following using vanishing points

Lane detection and tracking using B-Snake

“…Assuming the shapes of lane can be presented by either straight line [11,12,13,16] or parabolic curve [3,4,14,15], the processing of detecting lanes is approached as the processing of calculating those model parameters. This way, the model-based technique is much more robust against noise and missing data, compared with the feature-based technique.…”

“…This way, the model-based technique is much more robust against noise and missing data, compared with the feature-based technique. To estimate the parameters of lane model, the likelihood function [3,4,11,12,16], Hough transform [13], and the chi-square fitting [14,15], etc. are applied into the lane detection.…”

A multi-segment lane-switch algorithm for efficient real-time lane detection

“…This problem further persists owing to the lack of constraints on the shape or specifications of lane edges. Contrary to the feature-based approaches, using model-based techniques usually involves training a few parameters to represent a lane model, such as patterns like straight lines [14][15][16][17], parabolic curves [18][19][20][21], and B-spline snakes [22]. These models generally have a hypothesis that the shapes of lanes can be represented by either straight lines or a specific curve.…”

Real-Time Visual Sensing for Task Planning in a Field Navigation Vehicle

“…Some vehicle navigation applications have been reported in recent years, most of them related to road following in outdoor environments [1][2][3][4][5], and others related to indoor and structured scenes, where navigation is made inside a building and the main features to focus on are edges of corridors, walls, doors, etc. [6,7].…”