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This study describes a method for using a camera to automatically recognize the speed limits on speed-limit signs. This method consists of the following three processes: first (1) a method of detecting the speed-limit signs with a machine learning method utilizing the local binary pattern (LBP) feature quantities as information helpful for identification, then (2) an image processing method using...
Images projected from HUD (Head-up Display) are always overlaid with moving background scene. In such cases, drivers suffer from understanding instinctively the HUD information. Visibility enhancement of HUD information is very important for drivers to recognize easily and quickly the information. In this paper, we propose two visibility enhancement methods of HUD image, which are based on the dominant...
To achieve the goal of frontal vehicle detection in night-driving condition, we propose an effective method to detect the red taillights of vehicles. The challenge is that the taillight images captured with automatic exposure typically are overexposed, which makes red color segmentation often erroneous. Instead of customizing the camera hardware to tackle this problem, we combine morphological and...
In this paper, we propose a vision-based traffic light and arrow detection algorithm for intelligent vehicles. We detect all three traffic light colours along with the arrow direction robustly for varying illuminations and traffic lights. A fine-tuned convolutional neural network is used in an offline phase to localise the traffic light region-of-interest within a given camera image. Given the constrained...
In the field of intelligent vehicle systems (IVS), color and edge of lane markings are important features for vision-based applications. This paper proposes a method to detect lane marking based on a fusion approach which combine color and edge lane marking information. Firstly, by knowing the vehicle speed the road surface region of interest is extracted using the typical stopping distance. Secondly,...
Recently, detection and recognition of traffic panels and their textual information is studied increasingly to become the next working part of driver assistance systems and autonomous cars. These information are especially useful when other facilities fail to provide enough information about routes and places, like when Global Positioning System (GPS) gets blocked in high density urban areas. However,...
This paper presents the last developments towards vision-based target tracking by an AUV. The main concepts behind the visual relative localization are provided and the results from a statistical analysis for the relative localization algorithm are presented. The purpose of this analysis is to ensure properness of data used to feed controllers that are responsible for governing the AUV motion. A new...
This paper describes the Driver's dashboard implemented in AFV to display important vehicle parameters and a vision system display to perceive the environment for day and night time driving. The dashboard has been designed aesthetically such that it provides real time awareness of the vehicle condition by displaying the critical parameters which requires driver's attention for safe driving while automating...
Lane detection is one of the most challenging problems in machine vision and still has not been fully accomplished because of the highly sensitive nature of computer vision methods. Computer vision depends on various ambient factors. External illumination conditions, camera and captured image quality etc. effect machine vision performance. Lane detection faces all these challenges as well as those...
This paper proposes a method to detect the lanes from the aerial videos, which is composed of two parts: image pre-processing and the lane detection. The first part, image pre-processing, mainly includes down-sampling, image binarizing and lane edge getting, and then a low resolution binary image will be gotten. The second part consists of the line parameter getting based on Hough Transform, false...
The research described in this paper consists in developing a system for re-identifying people across multiple non-overlapping cameras. The proposed approach consists of three main steps: appearance-based feature extraction, data projection on manifold space, and similarity estimation for person re-identification. We first decompose the human image into a grid of patches and characterize each patch...
This paper presents a vision-based Leader-Follower cooperative scheme which consists of two underwater vehicles in the absence of explicit communications and direct information interchange. A novel method for implicitly calculating the relative pose between the two vehicles is introduced. The absolute and relative localization algorithm is solely based on the observation of visual features projected...
This paper describes a vision-based method of guiding autonomous vehicles within crop rows in agricultural fields where the crop rows are challenging to detect or their appearance is not known a-priori. The location of the crop rows is estimated with an SVM regression algorithm using colour, texture and 3D structure descriptors from a forward facing stereo camera pair. Our system rapidly learns a...
In this study, we developed a driver-assistance system on Lane Detection during nighttime by mounting a CCD camera inside the car to capture images and to use computer visions to detect lanes and the driving condition in front of the vehicle. This system can increase the safety of driving during low light condition. The features of this system includes: lane detection, surrounding vehicles detection,...
This paper addresses the challenging domain of vehicle classification from pole-mounted roadway cameras, specifically from side-profile views. A new public vehicle dataset is made available consisting of over 10000 side profile images (86 make/model and 9 sub-type classes). 5 state-of-the-art classifiers are applied to the dataset, with the best achieving high classification rates of 98.7% for sub-type...
Sudden brake seems to be unavoidable in driving practice to prevent from accidence. The sudden brake may often cause falling risks to on-board passengers in public transport and even threaten the lives of the senior. Thus, this paper presents an omnidirectional vision system to assist bus drivers in ensuring the safety for passengers. To this end, we configure an auxiliary camera in the boarding gate...
Research in traffic light recognition (TLR) has stagnated compared to related computer vision areas, such as pedestrian detection and and traffic sign recognition. We focus on the detection sub-problem, since this is the most challenging problem and solving this is the key to a successful TLR system. This is done by looking at four detectors from different author groups and their reported results...
Autonomous control of Flapping Wing Vehicles (FWVs) through sophisticated software units is challenging due to its inherent complex motion characteristics. This article emphasize on the development of graphical user interface (GUI) for the control of FWVs to achieve superior maneuverability. A vision based computer control interface is developed for manual as well as autonomous performance of FWVs...
When moving towards fully autonomous navigation, safety plays the most important role for both pedestrian and driver. This paper proposes a method to estimate the lane road region of interest based on the stopping typical distance of a vehicle required by the current speed of the vehicle. This was achieved by taking advantage of the difference in color of the road surface given by the lane marking...
The Unmanned Aerial System (UAS) market once belonged to professional companies only. Now many amateur pilots fly cheap, smartphone controlled models available in any electronic store. Due to altitude, speed, and weight, these flying objects can cause damage and injury. Hence, a way to manage them is necessary. This paper presents a UAS Traffic Management (UTM) system comprising three components:...
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