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Lane detection is a critical step in advanced driver assistance systems (ADAS). The detected lane information is used by later modules of warning and controlling the differential brake and steering angle. Here we propose an efficient algorithm for detecting accurate lane inbounds under varying illumination and road conditions like curvy, straight and dashed lane markings, deterministically. The current...
The goal of this work is the development of a low-cost driver assistance system that runs on an ordinary smartphone. It uses computer vision techniques and multiple-resolution template matching to detect speed limit signs and alert the driver if the speed limit is exceeded. It inputs an image of the sign to be detected and creates a set of multiple-resolution templates. It also inputs photographs...
The paper aims at providing an intelligent driver assistance system on mobile devices, which is mainly composed of the two parts - off road warning and distance warning of front vehicles. In this application, the paper proposes an efficient lane and front vehicles detection and tracking method which has been experiments on mobile phones. The method is proved to be efficient and practical even though...
The purpose of this paper is to propose a method to estimate the location of the vehicle within a road around a horizontal axis from the bird's eye perspective. This method uses a road heuristic — the edge length of the road, in order to localize a vehicle within the road. The method aims to determine erratic vehicle steering on roads using a single camera in places where lanes and road discipline...
Newly emerging, highly complex Advanced Driver Assistance Systems (ADAS) fuse the output of various system modules (e.g., lane detection, object classification). Such knowledge fusion is realized in order to gain additional information of the environment allowing for complex system tasks as path planning, the active search for specific objects and task-specific analysis of the environment. As part...
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