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With the rapid development and reduced cost of digital video capturing devices, driving video recorders (DVRs) begin to gain widespread popularity. What is seen and what happens along the way can thus be recorded in videos. However, searching for a specific scene or event among such massive video collections is laborious and tedious. In this paper, we develop a speed-adaptive street view image generation...
Nowadays, the technological and scientific research related to underwater perception is focused in developing more cost-effective tools to support activities related with the inspection, search and rescue of wreckages and site exploration: devices with higher autonomy, endurance and capabilities. Currently, specific tasks are already carried out by remotely-operated vehicles (ROV) and autonomous underwater...
Traffic density estimation plays an integral role in intelligent transportation systems (ITS), using which provides important information for signal control and effective traffic management. In this paper, we present a new framework for traffic density estimation based on topic model, which is an unsupervised model. This framework uses a set of visual features without any need to individual vehicle...
Reduced visibility on roadways caused by localized fog can impact the traffic flow in many ways: traffic speed, travel time delay, reduced capacity and accident risks. This paper presents a novel approach to estimate visibility conditions using an onboard camera and a digital map. Based on a traffic sign detector's characteristics in the fog, and registering detection by vision and information encoded...
The purpose of this paper is to evaluate the use of a micro aerial vehicle (MAV) for autonomous inspection and 3D reconstruction of underground mines. The goal is to manually fly an MAV equipped with cameras and a laser range sensor into a vertical shaft to collect data. This data can be used to evaluate the performance of the localization system as well as post processed to reconstruct a 3D model...
Visual based approach has been studied extensively for on-road vehicle detection, while it faces great challenges, as visual appearance of a vehicle may change greatly across different viewpoints, and partial observation happens sometime due to occlusions from infrastructure or scene dynamics, and/or limited camera vision field. Inspired by the works on part-based detection, this research proposes...
This paper proposes a camera-based visibility estimation method for a traffic sign. The visibility here indicates how a visual target is easy to be detected and recognized by a human driver (not a machine). This research aims at realizing a nuisance-free driver assistance system which sorts out information depending on the visibility of a visual target, in order to prevent driver distraction. Our...
This paper presents an autocalibration method to determine the pose of a stereo vision system based on knowing the geometry of the ground in front of the cameras. This pose changes considerably while the vehicle is driven, therefore it is good to know constantly the pose of the camera for several applications based on computer vision, such as advanced driver assistance systems, autonomous vehicles...
The vision based motion estimation has been investigated in the last few years. Although some progresses have been made in the assumption of planar, still there are no methods satisfying the high accuracy and real-time with absolute translation. This paper proposes a method to estimate vehicle motion by the fusion of omnidirectional camera and laser rangefinder to overcome the drawbacks mentioned...
This paper describes a method for estimating the 6-DoF viewing parameters of a calibrated vehicle-mounted camera. Visual features are combined with standard in-vehicle sensors and a single-track vehicle motion model in a bundle adjustment framework to produce a jointly optimal viewing parameter estimate. Results show that the vehicle motion model in combination with in-vehicle sensors exhibit good...
Driver assistance systems such as automatic steering for lane keeping are of particular importance for vehicle's lateral safety, and onboard look-ahead cameras are widely employed to acquire surrounding information for realization of such applications. In fact, vision-based lane keeping and automatic steering have been intensively studied in the past few decades. Meanwhile, electric vehicles, as green...
Human-symbiotic systems have been increasingly studied in recent years. Objective recognition by such systems often does not agree with subjective recognition by users. Therefore, it is an important to estimate users' subjective states appropriately. Information on what a user can see and what he/she cannot see in the environments is one of important clues to estimate his/her subjective states and...
This study specifically examines wall see-through visualization for drivers at blind corners to prevent crossing collisions. We believe that realizing the desired effect with the simplest visualization is a key to building practical systems, although previous studies mainly targeted rich visualization as if the wall were actually transparent. We compared several visualization levels using qualitative...
An autonomous wall inspection control based on a stereo optical flow, suitable for unmanned aerial vehicles endowed with a stereo vision system, is proposed in this paper. The inspection task consists of simultaneously controlling the inspection velocity along the surface, the relative yaw angle between the vehicle and the observed plane, as well as the orthogonal distance. A virtual spherical camera...
The aim of this work is to support a driver by notifying the information of traffic signals in accordance with their visibility. To avoid traffic accidents, the driver should detect and recognize surrounding objects, especially traffic signals. However, when driving a vehicle under rainy weather conditions, it is difficult for drivers to detect or to recognize objects existing in the road environment...
This paper is about long term navigation in dynamic environments. In previous work we introduced a framework which stored distinct visual appearances of a workspace, known as experiences. These are used to improve localisation on future visits. In this work we introduce a new introspective process, executed between sorties, thats aims by careful discovery of the relationships between experiences,...
Perception of the surrounding environment is one of the many tasks an automated vehicle has to achieve in complex and ever-changing surroundings. This typically includes several distinct sub-tasks, such as map-building, localisation, static obstacles detection, pedestrian detection,… Some of these tasks are nowadays very well known, such as map-building, whereas the perception, localisation and classification...
This paper addresses the problem of finding the host vehicle's lateral position on a multi-lane road, using information obtained by processing video sequences. A very important cue for lane identification is the class of the boundaries of the current lane. This paper presents a reliable solution for lane boundary type identification, based on frequency analysis of the gray level profile of these boundaries,...
The camera relative pose is essential information for driver assistance systems in general, and especially so for systems that aim to visualize obstacles or other relevant objects for the driver. In order to display objects that were not detected in the vision frame of the camera (e.g. road information of a digital map), the exact transformation from camera to the world has to be known for every time...
Reliable vehicle ego motion estimation based on visual information is an important research goal because it has applications like accurate long term localization by fusion with other sensors, temporal fusion between frames, moving obstacles detection and tracking, path planning etc. This paper evaluates and significantly improves some steps of existing visual odometry methods. The main contribution...
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