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This paper presents customized techniques for autonomous localization and mapping of micro Unmanned Aerial Vehicles flying in complex environments, e.g. unexplored, full of obstacles, GPS challenging or denied. The proposed algorithms are aimed at 2D environments and are based on the integration of 3D data, i.e. point clouds acquired by means of a laser scanner (LIDAR), and inertial data given by...
Recently, researches about Forward Collision Warning (FCW) technology has become one of the main parts of the development of Advanced Driver Assistance Systems (ADAS) to increase the road safety and develop autonomous vehicles. This paper presents a research about FCW based on monocular vision, which consists of two processes: vehicle detection and vehicle tracking. In the vehicle detection process,...
Modern vehicles are equipped with numerous driver assistance and telematics functions, such as Turn-by-Turn navigation. Most of these systems rely on precise positioning of the vehicle. While Global Navigation Satellite Systems (GNSS) are available outdoors, these systems fail in indoor environments such as a car-park or a tunnel. Alternatively, the vehicle can localize itself with landmark-based...
We introduce a new computer vision based system for robust traffic sign recognition and tracking. Such a system presents a vital support for driver assistance in an intelligent automotive. Firstly, a color based segmentation method is applied to generate traffic sign candidate regions. Secondly, the HoG features are extracted to encode the detected traffic signs and then generating the feature vector...
Microsleep is an involuntary episode of sleep which lasts for a fraction of a second or up to one minute where an individual fails to respond to their environment and becomes unconscious. Because of the lapsed time, microsleep can create dangerous situations, for example when a user is driving a car, any microsleep can result in unsafe situations or even death. In this paper, we design a system that...
This paper describes a vision-based multiple model adaptive estimation using UAVs that enables the tracking of a mobile target that changes the system model depending on unknown factors. In our system the machine-learning-based target identification method uses Haar-like classifiers that detects the target position. The system uses multiple extended Kalman filters for each system model and estimates...
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...
Humans are increasingly cooperating with machinery/robots in a high number of domains and under uncontrolled conditions. When persons are interacting with machinery, they are exposed to distraction/fatigue, which can lead to dangerous situations. The evaluation of individual's attention and fatigue levels is highly needed in such situations. This is an important measurement to avoid the interaction...
Video surveillance has been widely used in many applications. Public safety and theft protections are most important uses of it. A system like this needs an efficient transmission and storage of the large video data. Key frame extraction is a simple and powerful system to accomplish this objective. Keyframe extraction also called as a summary of the video because it gives the only important content...
Compressed domain moving object segmentation and classification plays an important role in many real-time applications, such as video indexing and intelligent video surveillance. Compared with the previous international video coding standards, such as H.264/AVC, HEVC introduces a host of new coding features. Therefore, moving object segmentation and classification directly from HEVC compressed videos...
Traffic sign detection and recognition plays an important role in driver assistance system especially in complexity environment. Firstly, RGB image is converted to standardization image only contained 8 colors for reducing computational burden. Only interesting color components are extracted as candidate region for further recognition. Then HOG descriptor is considered as detection characteristic...
In security surveillance at the perimeter of critical infrastructure, such as airports and power plants, approaching objects have to be detected and classified. Especially important is to distinguish between humans, animals and vehicles. In this paper, micro-Doppler data (from movement of internal parts of the target) have been collected with a small radar of a low-complexity and cost-effective type...
Moving targets induce unique micro-Doppler signatures. After conducting several measurements with human, vehicle, UAV and animal as targets using a 24 GHz radar, the micro-Doppler signatures are observed through time-velocity diagrams. A simple set of micro-Doppler features are then selected and extracted from the measurement data. Results show the potential of radar as a ground surveillance applications,...
Insufficient intersection management is one of the top congestion causes. Intersection performance enhancement requires its usage data and statistics, such as vehicle queue lengths, waiting times, etc. Intelligent Transportation Systems (ITS) provide transportation researchers and engineers with access to such data. However, the majority of the state of the art ITS are expensive, hard to maintain...
Todays, the number of vehicles is rapidly increasing. In parallel, the number of ways and traffic signs have increased. As a result of increased traffic signs, the drivers are expected to learn all the traffic signs and to pay attention to them while driving. A system that can automatically recognize the traffic signs has been need to reduce traffic accidents and to drive more freely. Traffic sign...
Moving targets induce unique micro-Doppler signatures. After conducting several measurements with human, vehicle, UAV and animal as targets using a 24 GHz radar, the micro-Doppler signatures are observed through time-velocity diagrams. A simple set of micro-Doppler features are then selected and extracted from the measurement data. Results show the potential of radar as a ground surveillance applications,...
Pedestrian detection is an important key problem in Advanced Driver Assistance Systems (ADAS). Un-signalized pedestrian crossing zone are dangerous places, where pedestrians enter the lane suddenly. This is the main factor for most of the accidents. For that, this paper illustrates a machine learning approach for detecting the pedestrian zone and also to detect the pedestrians crossing in that zone...
This paper proposed a new technique to determine the direction of a moving vehicle. In order to detect vehicles from road, concept of symmetrical descriptor is used to determine the ROI of each vehicle without using any motion features. This scheme proved to be advantageous as it does not require any background subtraction and efficiently works on real time applications. Once the vehicle is detected,...
One of the main recent research trends of the Italian Interuniversity Research Center on Integrated Systems for Marine Environment (ISME) is the use of marine cooperative teams of autonomous robots within the fields of security, prevention and management of emergencies at sea. Such fields are of worldwide interest for obvious reasons, but they have recently gained relevance in the current historical...
Driver fatigue is one of the most common reasons for deadly road accidents around the world. Continuous monotonous driving for long hours without rest causes drowsiness and consequently fatal road accidents. Automatic driver drowsiness detection can prevent a vast number of sleep persuaded road accidents, and hence can save precious lives. Number of techniques for driver drowsiness detection has been...
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