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In this work we present a method to automatically learn and detect cast shadows on highway surveillance scenarios. The first stage of this method uses a weak classifier as a pre-filter to select possible shadowed pixels in order to learn multi-layered statistical shadow models using a recursive Bayesian learning approach. These models will then be used, by a strong classifier, to correctly distinguish...
For a Driving Assistance System dedicated to intersection safety, knowledge about the structure and position of the intersection is essential, and detecting the painted road signs can greatly improve this knowledge. This paper describes a method for detection, measurement and classification of painted road objects that are typically found in European intersections. The features of the painted objects...
New methods based on vision have emerged in the area of mobile vehicle localization. Such methods offer an improved alternative in terms of accuracy to traditional localization methods like wheel odometry. In this paper we propose such a method that does not compromise precision and can run in real time. Depending on environment, feature numbers are sometimes insufficient. To solve this, our algorithm...
Depth accuracy is one of the most important characteristics for sensors used in distance estimation. Stereo-vision systems employ sub-pixel interpolation to achieve such accuracy. Literature in this domain is usually dedicated to simple window based stereo solutions. There are currently several new stereo algorithms developed to counter pixel level errors, but they neglect sub-pixel results. We propose...
Protection of critical transportation infrastructure such as railroad station is an important topic in these days. In this paper, we develop a new rule based approach to video surveillance system for detecting situations where pedestrians may be in peril, as well as suspicious action or interactions at railroad station. We analyze here two general types of pedestrian involved behaviors: (i) single...
Automatic vehicle detection systems in urban and inter-urban traffic using computer vision are frequently based on background subtraction methods. Moving shadows represent a serious difficulty for these methods, as they will appear as part of the segmented foreground vehicles. Shadow removal algorithms usually rely on exploiting color properties. However, the use of image color information, when available,...
Road segmentation is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. Significant efforts have been made in order to solve this task using vision-based techniques. The major challenge is to deal with lighting variations and the presence of objects on the road surface. In this paper, we propose a new road...
Occupancy grids have been used for a variety of applications in the field of robotics. These grids have typically been created based on data provided by range sensors such as laser or ultrasound. Current practice is to create the grids based on a probabilistic sensor model such as [1]. The use of stereovision to create occupancy grids is less common. This paper will detail a novel approach to compute...
This paper describes a new alternative procedure to improve the invariance to illumination changes on the image feature extraction provided by Harris corner detectors, using the local image moments information. Another alternative is presented for the matching process, which is enhanced adding local SURF descriptors. These both techniques are joined to give us a new promising visual guidance tool...
Track selective localization of railway vehicles is a precondition to more efficient logistics, improved security and autonomous driving. Often, satellite based navigation systems are used for localization tasks. However, in many cases, satellite navigation is not available or the sensor information is corrupted. To enhance availability and localization quality new sensors are needed. In this work...
This paper presents a new real time lane detection and tracking system which succeeds in sharp curved roads. The Warp Perspective Mapping (WPM) method was used to change the video image perspective to top view. A two dimensional Gabor filter and vertical pixel density calculation method was used to find initial lane regions. Second derivative approach of Composite Bezier spline fitting method calculates...
This paper proposes a real-time traffic sign detection system. In order to extract accurately the shape feature of the traffic sign, reduce the computational load and further improve the traffic sign detection rate, a novel approach based on surround suppression of texture edges and cascade detector is presented. The principle of surround suppression mainly adds a computational step to the canny edge...
In this paper the authors propose a new technique for determining a confidence factor applied to the performance prediction of individual luminaires within an overall pattern of luminaires. This work has relevance to any application where it is necessary to determine the performance of a lighting pattern e.g. street lighting, signal lighting etc. In this paper we apply our technique to a transportation...
Detection and classification of traffic signs is one of the most studied Advanced Driver Assistance Systems (ADAS) and some solutions are already installed in vehicles. Nevertheless these systems still have room for improvement in terms of speed and performance. When driving at high speed, warning systems require very fast processing of the video stream in order to lose as few frames as possible and...
Measuring distance to obstacles is an important process for intelligent vehicles (IV). With accurate measurement, IV can make appropriate maneuver to avoid such obstacles. To obtain highly accurate result, we used a Markov random field model-based global energy minimization algorithm called belief propagation (BP). However, BP has high computational complexity which makes it difficult for real-time...
Availability of detailed, high accuracy digital maps is crucial for many driver assistance applications. In this paper, a novel approach for automated map generation from aerial images is presented. Automatically generated maps present an alternative for applications that are not critical for vehicle safety such as accurate map based localization for route guidance. Aerial images as a source for automated...
This paper is focused on real time detection of satellite reception state. In constrained environment, such as urban areas, GNSS signals can be received directly, reflected or blocked by obstacles (building, vegetation, etc) and can lead to an error or a lack of positioning. This paper proposes to characterize the GNSS signals reception environment using image analysis. The proposed approach consists...
This paper presents a system used for navigating an autonomous vehicle through challenging traffic scenes based on stereo vision. In order to safely as well as legally facilitate autonomous driving behaviors such as road following, obstacle avoidance, off-road navigation, etc., the proposed system consists of two parallel modules: drivable road region detection and tracking module and painted lane...
The comprehension of dynamic objects in the environment is a major concern of prospective assistance systems. Among the relevant dynamic objects are not only road users, but also parts of the traffic infrastructure: Traffic lights switch between different light colors to manage traffic at intersections. We propose a camera-based approach to incorporate the visual information of traffic lights. Assistance...
This paper presents the results of an all-day-long pedestrian classification system based on an AdaBoost cascade meta-algorithm. The underlying idea is to use a Haar-features-based AdaBoost together with an ad-hoc-features-based AdaBoost system in order to reach a better pedestrian classification. A specific night-time pedestrian classification is developed in order to obtain a system that can be...
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