Hough Transform-based Road Boundary Localization

Abstract

The advanced driver-assistance system (ADAS) is designed to help drivers while they are driving. To help the drivers, ADAS first comprehends the situation by analyzing the data obtained from the road surroundings. In this process, the road boundary is one of the most important targets to detect for safe driving, but is frequently misdetected on crowded roads. Therefore, a new method for robustly detecting road boundaries on crowded roads is presented in this paper. First, road-boundary detection using a standard Hough transform is described, and its limitations are shown. Second, the cause of the limitations is explained by the measurement model of a laser scanner. Then, the standard Hough transform is modified to reflect the measurement model of the laser scanner; this change reduces the effect of closed obstacles. Finally, the proposed method is tested in the real-world environment, and it shows better performance than previous works in crowded environments.

3D Road Boundary Extraction Based on Machine Learning Strategy Using LiDAR and Image-Derived MMS Point Clouds

“…Model-based methods primarily focus on extracting road boundaries through model adaption, which makes the use of pre-existing information, such as road designs, dimensions, and curb heights. Initially, a parametric representation, such as a linear model [ 31 , 32 ], a clothoid model [ 17 ], or a ribbon snake model [ 18 ], is used to identify the shape of the road border. Next, a comprehensive boundary forecast based on the previous boundary model is created with different point labels, indicating roads or off-road areas.…”

Immersive Stereoscopic 3D System with Hand Tracking in Depth Sensor

“…The conventional 2D image based natural user interface [3][4][5][6] is sensitive to ambient illumination changes, and it is not enough to perceive performance degradation and the movement of human body moving in 3D space through 2D image. Therefore, fusion of 2D and 3D information is required [7][8][9]. Depth sensor based 3D hand tracking technology solves these problems and provides information to recognize human 3D hand movements in real time.…”