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This paper presents a full system for vehicle detection and tracking in non-stationary settings based on computer vision. The method proposed for vehicle detection exploits the geometrical relations between the elements in the scene so that moving objects (i.e., vehicles) can be detected by analyzing motion parallax. Namely, the homography of the road plane between successive images is computed. Most...
This study presents an effective method for detecting vehicles in front of the camera-assisted car during nighttime driving and implements it on an embedded system. The proposed method detects vehicles based on detecting and locating vehicle headlights and taillights using techniques of image segmentation and pattern analysis. Firstly, to effectively extract bright objects of interest, a segmentation...
Lane detection can provide important information for safety driving. In this paper, a real time vision-based lane detection method is presented to find the position and type of lanes in each video frame. In the proposed lane detection method, lane hypothesis is generated and verified based on an effective combination of lane-mark edge-link features. First, lane-mark candidates are searched inside...
People have a growing interest for driver assistant systems that are used to monitor the driving conditions by visual technique, and warn and guide drivers the road conditions. This paper proposes a real-time lane detection algorithm which is a necessary part for driver assistant system and unmanned vehicle. The algorithm presented in this paper integrates multiple cues, including bar filter which...
In this paper, we describe an effective version of an integrated system that combines vision-based object detection and vehicular ad-hoc networks (VANETs). With introduction of VANET in future years, data exchange between vehicles and infrastructure units will be possible and increase safety on roads. The number of vision-based active safety systems, like pedestrian detection and traffic sign recognition,...
Trustworthy sensors are the key points regarding road safety applications. The lack of reliable sensors able to fulfil the entire requirements for these situations makes fusion schemes mandatory. A fusion scheme that uses two sensors: far infrared camera vision and a laser scanner to perform pedestrian detection is presented. Both sensors have different field of view thus different detection zones...
Ground-truth data is essential for the objective evaluation of object detection methods in computer vision. Many works claim their method is robust but they support it with experiments which are not quantitatively assessed with regard some ground-truth. This is one of the main obstacles to properly evaluate and compare such methods. One of the main reasons is that creating an extensive and representative...
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...
Due to the recent progress in computer vision to interpret images and sequence of images, the video camera is a promising sensor for traffic monitoring and traffic surveillance at low cost. This paper focuses on the detection and tracking of multiple vehicles present in the field of view of a camera. Until now, the vehicle detection has been mainly performed by the widely used technique called background...
Lane departure warning Systems (LDWS) have recently become an integral part of many advance vision-based drive assistance systems. However, high cost and the requirement of professional installation have limited such systems to mostly commercial or luxury vehicles. To help bring the technology to the mainstream market, we have leveraged the popularity of smart phones and built SmartLDWS, the first...
This paper presents a real-time robust algorithm to automatically detect and classify round road signs on Chinese highways. As most of road signs on Chinese highways have circular borders, the detection system first takes advantage of a real-time circle detection algorithm to extract the regions of interest (ROI). Then the color and texture pattern in each ROI is analyzed and compared with sample...
We propose a novel method for automatically discovering key motion patterns happening in a scene by observing the scene for an extended period. Our method does not rely on object detection and tracking, and uses low level features, the direction of pixel wise optical flow. We first divide the video into clips and estimate a sequence of flow-fields. Each moving pixel is quantized based on its location...
This paper presents a lane detection and linear-parabolic lane tracking system using Kalman filtering method. First, the image horizon is detected in a traffic scene to split the sky and road region. Road region is further analyzed with entropy method to remove the road pixels. Lane boundaries are then extracted from the region using lane markings detection. These detected boundaries are tracked in...
This paper presents a real-time implementation on lane detection and tracking system in order to localize lane boundaries and estimate a linear-parabolic lane model. It is realized using TMS320DM642 DSP board. Video frame is first captured with CCD camera and stored in video port buffer. Next, input image is split into sky and road region with horizon localization. Lane analysis is applied on the...
This paper presents a vision-based road-barriers detection method. Because horizontal structures are hard to detect by binocular stereovision, object detection methods based on 3D points grouping fail to detect the barriers as obstacles and consequently specific ACC applications as longitudinal control will fail to react when the vehicle path is obstructed by such an object. Therefore the proposed...
Aiming to automatically judging if a driver is driving in violation of regulations at real time, the paper discusses recognition of driving across the central-line according to images taken by an on-board CCD image sensor. By use of image understanding and computer vision techniques, models have been established for perspective projection and vehicle's driving recognition across the central-line....
This paper presents an unstructured road detection algorithm which can improve the detecting speed and accuracy of unstructured road detection. In this algorithm, first, we process the original images with the median value filter, and suppress the stochastic noise; Then an Otsu multi-threshold algorithm based on two-peak method for rapid image segmentation is used, which cause the division effect...
This paper presents a new method based on digital image processing to realize the real-time automatic vehicle speed monitoring using video camera. Based on geometric optics, it first presents a simplified method to accurately map the coordinates in image domain into real-world domain. The second part is focused on the vehicle detection in digital image frames in video stream. Experiment shows it requires...
Based on computer vision principle and digital image differential detecting technology, we present a real-time method of vehicle's speed detection. First, calibrate parameters of camera, capture digital signal of images and take pre-processing on images. Then, select background image and set linear projection of speed. Finally, detect the moment of passing the linear projection of speed, and compute...
This paper proposes an improvement of advanced driver assistance system based on saliency estimation of road signs. After a road sign detection stage, its saliency is estimated using a SVM learning. A model of visual saliency linking the size of an object and a size-independent saliency is proposed. An eye tracking experiment in context close to driving proves that this computational evaluation of...
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