The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this research paper Objects are detected and recognized in cluttered scene. We use Harris Corner Detector to extract interest points, and use additional descriptor FREAK (Fast Retina Keypoint) to match and find detect the object. We also use some classification algorithm to classify and label the object based on the extracted features. The proposed techniques are precise and robust.
Vehicle and Pedestrian Detection is a key problem in computer vision, with several applications including robotics, surveillance and automotive safety. Much of the progress of the past few years has been driven by the availability of challenging public datasets. In this paper, we build up a vehicle and pedestrian detection system by combing Histogram of Oriented Gradients (HoG) feature and support...
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...
It is dangerous that changing lane without knowing the information of the other lane in the blind-spot area. We propose a vision based lane changing assistance system to monitor the vehicle in the blind-spot area. So far in the literature, only few results are found using the features of the vehicle to detect the vehicle. Without using features from vehicle, to conclude that vehicles do appear in...
Intelligent vehicle lighting systems aim at automatically regulate the headlights' beam angle so as to illuminate as much of the road ahead as possible, while avoiding dazzling other drivers. A key component of such a system is a computer vision software able to distinguish blobs due to vehicles' head and rear-lights from those originating from road lamps and reflective elements like poles and traffic...
Various image processing techniques and geometric models have been applied in vision based lane detection subsystems of intelligent vehicles and Advanced Driver Assistance Systems (ADAS). However, challenging conditions such as strong shadows, occlusions, eroded markings, high curvatures are ongoing issues in this topic. In this paper, a novel lane extraction method based on symmetrical local threshold...
A new method for real-time detection and tracking of multiple moving vehicles from traffic video is proposed. This method first uses MoG and texture based model to extract foreground from the scene, then detect moving targets using a modified version of timed motion history image (tMHI), and finally uses Kalman prediction filter to track these targets, which the full moving trajectories of the targets...
Road detection is a vital task for the development of autonomous vehicles. The knowledge of the free road surface ahead of the target vehicle can be used for autonomous driving, road departure warning, as well as to support advanced driver assistance systems like vehicle or pedestrian detection. Using vision to detect the road has several advantages in front of other sensors: richness of features,...
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...
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 presents a vision based scheme for detecting flying vehicle using a new feature extraction and correspondence algorithm as well as a motion flow vectors classifier. The base of detection is to classify the motion flow vectors of object and scene at two video sequences from a mobile monocular CCD camera. For this purpose, we introduce a method to extract robust features from fuzzified edges...
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...
Detection of license plate is an important process in intelligent transportation systems before license plate recognition. In this paper, we proposed an autonomous license plate detection system with computer vision instead of sensors. Using characteristics of dynamic images, our system rapidly identifies the license plate region. The system consists of two subsystems: car detection subsystem and...
In many driver assistance systems and autonomous driving applications, both LIDAR and computer vision (CV) sensors are often used to detect vehicles. LIDAR provides excellent range information to different objects. However, it is difficult to recognize these objects as vehicles from range information alone. On the other hand, computer vision imagery allows for better recognition, but does not provide...
This paper studies some aspects needing to be improved in current video supervision technology. It puts forward video supervision background self-adaptive algorithm in complex environment, by using mathematical morphology, genetic algorithm, rough set theory, etc. We construct morphological structure element according with traffic moving target, and propose mathematical morphology analysis model for...
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,...
In this paper, we present a two-stage vision-based approach to detect front and rear vehicle views in road scene images using eigenspace and a support vector machine for classification. The first stage is hypothesis generation (HG), in which potential vehicles are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map to create potential regions where vehicles...
This paper presents a new method for the detection and 3D reconstruction of the road lane using onboard stereovision. The proposed algorithm makes it possible to overcome the assumptions commonly used in most of the detection systems using monocular vision such as: flat road, constant pitch angle or absence of roll angle. The proposed method of detection and 3D reconstruction is based on two modules...
Currently available methods for object recognition and classification primarily rely on static information in single-frame images. However, for the combat aerial video (usually low resolution video), all these static indexes used for object classification and recognition are almost impossible to obtain. To address this challenge, we propose an innovative 3D and dynamic semantic scene analysis based...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.