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We present a novel visual obstacle detection and tracking system based on stereo vision. A robust stereo matcher, an obstacle detector and a tracker module are implemented and tested under actual driving conditions. Implemented system shows reliable range estimation, detection and tracking performance. Our system has showed 82.4 percent correctly detected rate in complex traffic situations.
Target detection system based on visible image sensor is applied in many fields. In vehicle detection field, people are now paying more and more attention to the research on finding a real-time vehicle detection system and algorithm with preferable precision. This paper designs a real-time system based on digital signal processing (DSP) TMS320DM643 and proposes a fast and robust corner detection algorithm...
In vision navigation tasks, lane marks on roads are very important vision cues. Usually, these lane marks can be detected using Hough transform or vanishing point detection. However such methods always need great computing power, and they are difficult to be realized on board processors in real-time. In this paper, a vanishing point like reference point is set as a support vector. The points on the...
In this paper, we present a computationally efficient and robust lane detection algorithm based on Hough transform. The proposed method first extracts lane markings by applying 1D ridge detector to each row of an image. Given the extracted ridge points, the lane is then detected by applying Hough transform. Unlike the conventional methods, we consider only small set of line candidates which pass through...
An improved monocular vision method is studied for intelligent vehicle to detect the preceding car in the structural road environment. Through identifying the edges of the car, the object is detected; the false object is eliminated and the eligible object expressed as a 2-D model is acquired. Then the location of object in the next frame is predicted by Kalman filter, and the object is detected near...
This paper describes hybrid fusion module used in a strong localization context (POMA) for embedded vehicle applications. This work has been developed in order to give an answer to the POMA (Positioning, Maps and local referencing) sub project objectives. These objectives are to provide, for a set of high level applications, a positioning service included a service quality, a metric accuracy (lane)...
An effective lane detection algorithm is a basic, yet fundamental component of both autonomous navigation and advanced road safety systems; this paper presents an approach that produces reliable results exploiting a robust polyline matching technique. The proposed solution has been designed from the ground up so that only very limited hardware resources are required: just one camera is used, and the...
In this paper, we present improved lane tracking using vehicle localization. Lane markers are detected using a bank of steerable filters, and lanes are tracked using Kalman filtering. On-road vehicle detection has been achieved using an active learning approach, and vehicles are tracked using a Condensation particle filter. While most state-of-the art lane tracking systems are not capable of performing...
The video-based on-road detection of vehicles at daytime allows driver assistance systems to avoid collisions and thereby improve safety, and realize comfort functions, like the well known adaptive cruise control. However, at nighttime, common video sensor based vehicle detection algorithms can't be used, because most state-of-the-art features, like shadows, symmetry and others, cannot be measured...
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...
This paper presents a robust vehicle license plate detection algorithm based on multi-features, including mathematical morphology, rectangle features, edge statistics and characters features. Here we utilize the word ??robust?? to describe the proposed algorithm because it is not only adaptive to variance occasions, such as variance of the illumination, vehicle position, the color, both background...
Occlusion in the monitoring video is a problem often encountered in the moving vehicles detection, tracking and identification. In practice, the moving vehicles that are needed to be tracked are often overlapped in the image. As a result, the mistakes in the targets segment and traffic parameters calculation are the problems much more difficult to solve. Generally, the moving target occlusion in video...
Lane detection is one of fundamental but critical problems for lane following system of intelligent vehicles. However, a robust and cost effective approach is still a deserve exploit issue. A novel and effective approach using a five steps scheme is presents. First, Canny detector is used to obtain edge map from the road image acquired from monocular camera mount on vehicle; Second, a matching process...
Traffic data extraction is an increasing demand for applications such as traffic lights control, population evacuation, or to reduce traffic issues including congestion, pollution, delays, and accidents. We present in this paper a new framework to reliably detect, classify and track multiple vehicles at night-time. The system shows excellent performance after an evaluation procedure involving many...
In this paper, we present the automatic real time stereo tracking algorithm we devised to derive the 3D orientation of the longitudinal axis of a vehicle by recovering its trajectory during a motion sequence. An accurate identification of vehicle's longitudinal axis is required in automotive applications where measurements achieved by testing apparatus must be in compliance with regulations. Usually,...
This paper presents a robust traffic parameters extraction (RTPE) method for intelligent traffic system. Firstly a texture-based algorithm is introduced to solve the moving shadow problem, which occurs in traffic lane commonly. Secondly, we propose a robust exponential entropy-based and data-dependent threshold vehicle detection algorithm, named RVD-EXEN algorithm to extract vehicle's feature from...
One key goal of current Computer Vision research activities is to provide robust systems for improving Transport safety through the use of Information Technology. Recent advances allow public environments (such as train stations or, simply, the street) under video surveillance to be modelled by means of the detection, tracking, and identification of the different elements in it (passengers, road,...
A novel vehicle localization algorithm based on phase information and contour projection is proposed. Firstly, HSV color model and RGB color model are combined, and contours of the vehicles in image are detected based on phase congruency. Secondly, contour projection method is utilized to get candidate vehicle regions. Finally vehicle region distinguishing algorithm are applied to the candidates,...
A real-time monocular vision based rear vehicle and motorcycle detection and tracking approach is presented for lane change assistant (LCA). To achieve robustness and accuracy this work detects and tracks multiple vehicles and motorcycles on road by combining multiple cues. To achieve real-time multi-resolution technology is used to reduce computing complexity, and all algorithms have been implemented...
This paper presents an information-fusion-based approach to the estimation of urban traffic states. The approach can fuse online data from underground loop detectors and global positioning system (GPS)-equipped probe vehicles to more accurately and completely obtain traffic state estimation than using either of them alone. In this approach, three parts of the algorithms are developed for fusion computing...
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