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In this study, model-referenced pose estimation using monocular vision is applied to the navigation of an underwater vehicle in an underwater environment. The relative spatial information between the vehicle and the nearby underwater structure is obtained by employing 3D model-referenced tracking techniques. The obtained relative pose enables the underwater robot to localize around the underwater...
It is still hard mission for human divers or robotic systems to investigate complex underwater environments, composed of several turning points and rooms. This paper explains a design of the Autonomous Underwater Vehicle (AUV) for marking physical and visible path logs in water. Then, it will make the repeated exploration easier. For the solution of underwater marking, we chose to use paraffin wax...
Computation of Visual Rear Ground Clearance of vehicles is an important computer vision application. This problem is challenging as the road and vehicle rear bumper may have subtle appearance differences, vehicle motion is on uneven surfaces and there are real-time considerations. In this paper a method is presented to compute the Visual Rear Ground Clearance of a vehicle from its rear view video...
Over the last decade, there have been many studies that focus on modeling driver behavior, and in particular detecting and overcoming driver distraction in an effort to reduce accidents caused by driver negligence. Such studies assume that the entire onus of avoiding accidents are on the driver alone. In this study, we adopt a different stance and study the behavior of pedestrians instead. In particular,...
This paper proposes methods for detecting platoons in a traffic stream using automated techniques. Three different methods are tested for platoon detection, namely Cluster based approach, modified Gaur and Mirchandani approach, and an Image processing based technique. Corroboration was carried out using dataset from an arterial in Chennai, India. The results obtained showed all the methods working...
Advanced Driver Assistance Systems (ADAS) towards autonomous driving require an ego vehicle localization on maps to be able to use the map data for e.g. behavior and trajectory prediction of traffic participants.
With the fast development of Geographic Information Systems, visual global localization has gained a lot of attention due to the low price of a camera and the practical implications. In this paper, we leverage Google Street View and a monocular camera to develop a refined and continuous positioning in urban environments: namely a topological visual place recognition and then a 6 DoF pose estimation...
This article presents a bathymetric SLAM (simultaneous localization and mapping) solution for underwater vehicles by addressing the registration of point clouds gathered from single line laser-based structured light systems. While structured light can be applied to generate millimetre resolution seafloor bathymetry, the accuracy of the maps generated is typically constrained by the localization accuracy...
The research community has shown significant improvements in both vision-based detection and tracking of vehicles, working towards a high level understanding of on-road maneuvers. Behaviors of surrounding vehicles in a highway environment is found as an interesting starting point, of why this dataset is introduced along with its challenges and evaluation metrics. A vision-based multi-perspective dataset...
This paper presents a vehicle navigation system that is capable of achieving sub-meter GPS-denied navigation accuracy in large-scale urban environments, using pre-mapped visual landmarks. Our navigation system tightly couples IMU data with local feature track measurements, and fuses each observation of a pre-mapped visual landmark as a single global measurement. This approach propagates precise 3D...
In recent years, there has been an interest in detailed monitoring of road traffic, particularly in intersections, in order to obtain a statistical model of the flow of vehicles through them. These models aid in the optimization of traffic management and allow for smarter transportation systems. While conventional methods sensors at each of the intersections entrances/exits allow for counting, are...
In recent years, great technological subsurface advancements have been made to observe and study Carcharodon carcharias, white sharks with autonomous underwater vehicles (AUVs) [1]. Prior to 2011, tracking pelagic predators like sharks was limited to using active tracking from boats [2] and passive acoustic arrays [3]. These aforementioned techniques proved to be limited by logistics such as weather...
This paper presents an agile approach to facilitate the rapid development of traffic sign classification algorithms in heavy vehicles under a wide range of visibility conditions. A vision-based traffic sign recognition system makes a significant contribution to improving the transportation safety by enhancing the driver's awareness on important road signs in an automotive cockpit environment. It has...
Fast expansion of Advanced Driver Assistance Systems (ADAS) market and applications has resulted in a high demand for various accompanying algorithms. In this paper we present an implementation of Driver monitoring algorithm. Main goal of the algorithm is to automatically asses if driver is tired and in that case, raise a proper alert. It is widely used as a standard component of rest recommendation...
Kangaroo vehicle collisions are a serious problem threatening the safety of the drivers on Australian roads. It is estimated, according to a recent report by Australian Associated Motor Insurers, that there are around 20,000 kangaroo vehicle collisions during year 2015 in Australia. As a result, more than AU \$75 million in insurance claims, and a number of animal and human severe injuries and fatalities...
This paper describes a real-time method for building 3D feature models of an object of interest, e.g. a vehicle. The model generation works unsupervised and consists of four recursive steps. The first two steps identify the object of interest and extract the object-related sensor data. In the third and fourth step, prominent features are detected and integrated into a common 3D feature model. This...
Unfamiliar urban intersections pose high demand on drivers. They are not only engaged in correctly assessing large amount of visual stimuli, including multiple diverse moving objects (e.g. other vehicles, pedestrians, cyclists) but also actively processing instructions provided by navigation system, either in-car or on other devices such as smart-phones. In such a highly dynamic and engaging situation,...
Existing approaches to object detection address the generation of object hypotheses by extracting several cues in natural and automotive images, relying on objects with sufficiently high resolution. Very little to almost no approaches, however, address the generation of hypothesis of very small or distant objects in images such as on motorways. Here, we propose a simple yet effective approach to generating...
To be able to predict the evolution of the driving context, estimate the expected risks and plan future behavior alternatives, it is crucial to know where traffic participants can go and where they will most likely go. Consequently, for future Advanced Driver Assistance Systems (ADAS), precise, lane-accurate localization of the ego- as well as the other vehicles is a key technology. The proposed standard...
This paper aims to develop a control algorithm for a unicycle type AGV (Automated Guided Vehicle) to follow a trajectory predefined by a line avoiding oscillation on its movements. At the first tests the PID controller will be applied. On some applications cameras are used to help a robot follow a track (instead of infra red sensors), determining if it should keep a forward movement or turn to any...
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