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To enable an effective traffic management and signal control, it is important to know the road traffic density. In recent years, video surveillance based systems and monitoring tools have been widely used for obtaining road traffic density for traffic management. To address the needs of autonomous traffic data extraction and video analysis, a vast body of research exists. However, these schemes are...
Many applications of machine-to-machine (M2M) based intelligent transportation systems highly rely on the accurate estimation of neighbor map, where neighbor map mentions the locations of all nearby vehicles and pedestrians. To build the neighbor map, it usually integrates multiple sensors, such as GPS, odometer, inertial measurement unit (IMU), laser scanners, cameras, and RGB-D cameras. In this...
This paper proposes a novel approach of developing a vision-based forward collision warning system (V-FCW) under an integrated platform with both V-FCW algorithm development and field-test data driven system verification. The developed verification platform provides huge amount of video data collected from field testing under various real driving conditions with labeled ground truth and fast search...
We present a multiscale adaptive search algorithm for efficiently searching an unknown number of stationary targets using a team of multiple mobile sensors. We first derive a Spectral Multiscale Coverage (SMC) control law for a Dubins vehicle model. Given a search prior, the SMC control leads to uniform coverage dynamics for the mobile sensors such that the amount of time spent observing a region...
In this paper we propose a vehicle detection framework on low resolution aerial range data. Our system consists of three steps: data mapping, 2D vehicle detection and postprocessing. First, we map the range data into 2D grayscale images by using the depth information only. For this purpose we propose a novel local ground plane estimation method, and the estimated ground plane is further refined by...
Visually estimating a robot's own motion has been an active field of research within the last years. Though impressive results have been reported, some application areas still exhibit huge challenges. Especially for car-like robots in urban environments even the most robust estimation techniques fail due to a vast portion of independently moving objects. Hence, we move one step further and propose...
In this paper we propose an approach for dynamic scene perception from a moving vehicle equipped with a stereo camera rig. The approach is solely based on visual information, hence it is applicable to a large class of autonomous robots working in indoor as well as in outdoor environments. The proposed approach consists of an egomotion estimation based on disparity and optical flow using the Longuet-Higgins-Equations...
An advanced method for road course estimation is presented. It is based on the state-of-the-art Kalman filter lane detection and allows for a robust sensor-based estimation of road courses in great distances. Only the parameters for the road course are estimated which results in a reduced parameter space and therewith more robustness. Instead of laterally displaced single feature points tangential...
This paper proposes a novel vehicle detection system based on shift of a feature plane, which consisted of feature points on a front surface of vehicle, using in-vehicle camera for following vehicles' observation. We find that the feature plane of the vehicle's front surface shifts in accordance with the affine transform. We perform experiments and evaluate performances of our system. As results,...
This paper presents a computer vision-based approach to tracking surrounding vehicles and estimating their trajectories, in order to detect potentially dangerous situations. Images are acquired using a camera mounted in the egovehicle. Estimations of the distance, velocity and orientation of other vehicles on the road are obtained by detecting their lights and shadow. Because 3D information is not...
This paper presents an application of the moving target detection by focusing technique (MTDF) in civil traffic monitoring. The experimental results based on simulations show that the basic civil traffic monitoring can be solved using MTDF using a single-channel airborne SAR system. With an assumption of known moving directions of vehicles, MTDF allows detecting, estimation of speed, and finally reconstructing...
Vision-based autonomous vehicles must face numerous challenges in order to be effective in practical areas. Among these lies the detection and localization of independent-moving objects, so as to track or avoid them. In this paper a method that address this particular issue is presented. Information from stereo and motion is used to extract the ego-motion of the vehicle. Known defects of this estimation...
This contribution presents a lane estimation system for night applications which covers distances up to 140 m in rural environment. The high detection range is essential for upcoming warning systems to decide whether a detected object is on the road and thus of immediate importance for the driving task. In order to realize a robust lane detection system we present a fusion system that combines the...
Vehicle velocity estimation is an important aspect of intelligent transportation systems. Normally velocity is estimated using dedicated laser speed traps and Doppler radars. Recently, the use of cameras is becoming more common for the purpose of traffic surveillance and smart surveillance system. It is thus the aim of this paper to propose a method for vehicle speed estimation using these existing...
In using image analysis to assist a driver to avoid obstacles on the road, traditional approaches rely on various detectors designed to detect different types of objects. We propose a framework that is different from traditional approaches in that it focuses on finding a clear path ahead. We assume that the video camera is calibrated offline (with known intrinsic and extrinsic parameters) and vehicle...
This paper proposes a new background subtraction algorithm based on the sigma-delta filter, which is intended to be used in urban traffic scenes. The original sigma-delta algorithm is a very interesting alternative due to its high computational efficiency. However, the background model quickly degrades in complex urban scenes because it is easily “contaminated” by slow-moving or temporarily stopped...
Vehicle classification is very important in traffic flow analysis for traffic monitoring systems. Accurate estimation of wheel baseline length can provide a useful cue for vehicle classification. In this paper, we propose a new method for detecting accurate wheel center points and estimating the wheel baseline length of a vehicle taking the distortion in the circular fisheye images into consideration...
This paper presents a novel approach for an online initial camera calibration to estimate the extrinsic parameters for vision-based intelligent driver assistance systems. The method uses the periodicity of dashed lane markings and velocity information to determine the extrinsic camera parameters: height, pitch and roll angle. A lane marking detector is utilized to convert the images of road scenes...
Forward Collision Warning (FCW) together with Lane Departure Warning (LDW) and Electronic Stability Control (ESC) can highly contribute to a safer traffic environment. Therefore those three systems will be supported by the US NCAP (New Car Assessment Program) until the end of 2009 and rewarded in the new active safety rating. LDW and ESC are already on the market whereas development on the first vision-based...
This paper presents a new method to improve the perception of the environment of a vehicle. The aim here is to detect the vehicles using a scanning laser range finder and track the detected objects at each time. This contribution can be considered as an element of a global vehicle-to-vehicle (v2v) surveillance system where the on-board system receives warnings from the other local systems. It allows...
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