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In this paper we present a method for calculating inertial motion feedback in a teleoperation setup. For this we make a distinction between vehicle-state feedback that depends on the physical motion of the remote vehicle, and task-related motion feedback that provides information about the teleoperation task. By providing motion feedback that is independent of vehicle motion we exploit the spatial...
Most of the fatal injuries and the loss of lives occur due to lack of timely and quick action to be taken by the vehicular drivers. The difficulty in determining the incidence of fatigue-related accidents is due to the difficulty in identifying fatigue as a causal or causative factor in accidents. In most instances, one or more indirect or circumstantial pieces of evidence are used to make the case...
This paper explores using the first subsymbol in the structure of a GFDM symbol as a pseudo circular preamble. As data and training sequence overlap in the GFDM structure, an initial estimation approach for isolating the preamble information from the data is presented. The concept allows for adaptation of state-of-the-art techniques developed for OFDM in order to estimate time offset at every GFDM...
Because driver's action cannot be remembered and reappeared during tank steer training, whose skill is estimated only by teacher's subjective judgment. In order to solve this problem, some new methods are designed, which include using operating lever displacement to record driver's activity, using state changing matrix to reflect driver's operation process, using activities sequence of steer rule...
The application of kernel function made support vector machine one of the research focuses in machine learning field. However, single kernel function is difficult to process complex data efficiently. Multiple kernel method is a common solution for this problem in recent years. The commonly used multiple kernel function is a weighted combination of different kernel function. It lacks the pertinence...
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...
Image analytics, biometrics access control, security, and surveillance applications utilize complex machine learningand computer vision algorithms, such as face detection andrecognition. Speedup and accuracy are two important factorsthat need to be addressed in all such complex applications. Parallel computing breaks down the complex tasks into discretefragments to be solved concurrently on multiple...
Globally, safety technology of smart cars is developing for drivers' safety. Because the eye inspection of tire pressure is difficult, automatic sensing of the tire pressure is very important. Tire pressure monitoring system measures tires' pressure and temperature. By using TPMS system we can reduce pollution emissions, fuel consumption and car accident. U.S.A NHTSA made a law to use TPMS on cars...
Light detection and ranging (LIDAR) scanners are essential components of intelligent vehicles capable of autonomous travel. Obstacle detection functions of autonomous vehicles require very low failure rates. With the increasing number of autonomous vehicles equipped with LIDAR scanners to detect and avoid obstacles and navigate safely through the environment, the probability of mutual interference...
In the paper, comparative studies of three projection systems was carried out, i.e., With a cylindrical screen, with rear projection on foil placed on car windows -- "on screen", and with a collimation system. The purpose of the study was to assess the performance characteristics of visualization systems and the susceptibility of trainees to symptoms of simulator sickness. The results indicated...
While much work in the domain of traffic lights recognition is invested in the detection of traffic lights, classification of their exact state (including color phase and possible arrow pictogram) is often neglected. In this paper, we propose a robust approach for efficient video-based classification of said state with particular attention to the displayed pictogram and an additional ability to reject...
Concerns about global warming and energy costs have induced transport companies to take measures to reduce fuel consumption. Among the different options available, efficient driving is widely used, allowing a reduction in fuel consumption of around 10%. However, changing the driver's behavior is not exempt of problems. The success of efficient driving techniques in the long term is related to the...
Vision-based localization on robots and vehicles remains unsolved when extreme appearance change and viewpoint change are present simultaneously. The current state of the art approaches to this challenge either deal with only one of these two problems; for example FAB-MAP (viewpoint invariance) or SeqSLAM (appearance-invariance), or use extensive training within the test environment, an impractical...
The detection of vehicles driving on busy urban streets in videos acquired by airborne cameras is challenging due to the large distance between camera and vehicles, simultaneous vehicle and camera motion, shadows, or low contrast due to weak illumination. However, it is an important processing step for applications such as automatic traffic monitoring, detection of abnormal behaviour, border protection,...
Commercial motor vehicles are mandated to display a valid U.S. Department of Transportation (USDOT) identification number on the side of the vehicle. Automatic recognition of USDOT numbers is of interest to government agencies for the efficient enforcement and management of the commercial trucks. Near infrared (NIR) cameras installed on the side of the road, to capture an image of an incoming truck,...
The number plate detection is a key step affecting the overall performance of the number plate recognition system. In the paper a novel algorithm for this purpose is proposed. The approach is based on the detection of text areas using the stroke width transform. More plate candidates are detected using the specifically developed image preprocessing scheme based on set of morphological operators and...
Tactics are the part of the military problem solving, which attempts to address situations that arise in a concrete context and in a specific geographical area. It is about learning to perceive both the more stable geographical conditions in the working area as well as taking into consideration the effects of climate and weather and how the squad and their systems are affected and how an opponent...
Detecting objects such as humans or vehicles is a central problem in video surveillance. Myriad standard approaches exist for this problem. At their core, approaches consider either the appearance of people, patterns of their motion, or differences from the background. In this paper we build on dense trajectories, a state-of-the-art approach for describing spatio-temporal patterns in video sequences...
Obstacle detection for advanced driver assistance systems has focused on building detectors for only a few number of object categories so far, such as pedestrians and cars. However, vulnerable obstacles of other categories are often dismissed, such as wheel-chairs and baby strollers. In our work, we try to tackle this limitation by presenting an approach which is able to predict the vulnerability...
Traditionally, an adaptive boosting (AdaBoost) algorithm is used for object recognition because of its prevalent usage and well-trained results. However, because the computation of AdaBoost is extremely time-consuming, it is difficult to guarantee that the computations reflect the latest information in real time. To speed-up the operation, the original AdaBoost algorithm was accelerated with a graphics...
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