386 research outputs found
Model-Based Estimation of Meteorological Visibility in the Context of Automotive Camera Systems
Highly integrated and increasingly complex video-based driver assistance systems are rapidly developing nowadays. Following the trend towards autonomous driving, they have to operate not only under advantageous but also under adverse conditions. This includes sight impairments caused by atmospheric aerosols such as fog or smog. It is an important part of environmental understanding to thoroughly analyze the optical properties of these aerosols.
The aim of this thesis is to develop models and algorithms in order to estimate meteorological visibility in homogeneous daytime fog. The models for light transport through fog are carefully derived from the theory of radiative transfer. In addition to Koschmieder's well-established model for horizontal vision, a recursively-defined sequence of higher-order models is introduced which yields arbitrarily good approximations to the solutions of the radiative boundary problem.
Based on the radiative transfer models, visibility estimation algorithms are proposed which are applicable to data captured by a driver assistance front camera. For any one of these algorithms, the recording of luminances from objects observed at distinct distances is required. This data can be acquired from moving objects being tracked as well as from depth-extended homogeneous objects such as the road. The resulting algorithms supplement each other with respect to different road traffic scenarios and environmental conditions. All given algorithms are extensively discussed and optimized regarding their run-time performance in order to make them applicable for real-time purposes. The analysis shows that the proposed algorithms are a useful addition to modern driver assistance cameras
Persistent phosphor SrAl2O4:Eu,Dy in outdoor conditions : saved by the trap distribution
Persistent phosphors are a specific type of luminescent materials having the unique ability to emit light long after the excitation has ended. They are commonly used as emergency signage in near ideal, isothermal indoor situations. Recently, their energy storage capacity was relied on for outdoor situations, e.g. for glow-in-the-dark road marks and in combination with solar cells and photo catalytic processes. In this work the influence of temperature, illumination intensity and the duration of the night is critically evaluated on the performance of afterglow phosphors. The persistent luminescence of SrAl2O4:Eu,Dy green emitting phosphors is studied under realistic and idealized conditions. It is found that the light output profile is hardly influenced by the ambient temperature in a wide range. This is due to the presence of a broad trap depth distribution, which is beneficial to cover the longer and colder winter nights. Temperature drops during the night are however detrimental. For traffic applications, the total light output of glow-in-the-dark road marks at the end of the night is not sufficient for the studied compound, although re-charging by the car's headlamps partially alleviates this. For energy storage applications, the trap density should be improved and tunneling recombination processes might be needed to overcome overnight temperature drops. (C) 2015 Optical Society of Americ
Visibility And Confidence Estimation Of An Onboard-Camera Image For An Intelligent Vehicle
More and more drivers nowadays enjoy the convenience brought by advanced driver assistances system (ADAS) including collision detection, lane keeping and ACC. However, many assistant functions are still constrained by weather and terrain. In the way towards automated driving, the need of an automatic condition detector is inevitable, since many solutions only work for certain conditions. When it comes to camera, which is most commonly used tool in lane detection, obstacle detection, visibility estimation is one of such important parameters we need to analyze.
Although many papers have proposed their own ways to estimate visibility range, there is little research on the question of how to estimate the confidence of an image. In this thesis, we introduce a new way to detect visual distance based on a monocular camera, and thereby we calculate the overall image confidence.
Much progresses has been achieved in the past ten years from restoration of foggy images, real-time fog detection to weather classification. However, each method has its own drawbacks, ranging from complexity, cost, and inaccuracy.
According to these considerations, the new way we proposed to estimate visibility range is based on a single vision system. In addition, this method can maintain a relatively robust estimation and produce a more accurate result
Image based analysis of visibility in smoke laden environments
This study investigates visibility in a smoke laden environment. For many years, researchers and engineers in fire safety have criticized the inadequacy of existing theory in describing the effects such as colour, viewing angle, environmental lighting etc. on the visibility of an emergency sign. In the current study, the author has raised the fundamental question on the concept of visibility and how it should be measured in fire safety engineering and tried to address the problem by redefining visibility based on the perceived image of a target sign. New algorithms have been created during this study to utilise modern hardware and software technology in the simulation of human perceived image of object in both experiment and computer modelling. Unlike the traditional threshold of visual distance, visibility in the current study has been defined as a continuous function changing from clearly discemable to completely invisible. It allows the comparison of visibility under various conditions, not just limited to the threshold. Current experiment has revealed that different conditions may results in the same visual threshold but follow very different path on the way leading to the threshold. The new definition of visibility has made the quantification of visibility in the pre-threshold conditions possible. Such quantification can help to improve the performance of fire evacuation since most evacuees will experience the pre-threshold condition. With current measurement of visibility, all the influential factors such as colour, viewing angle etc. can be tested in experiment and simulated in numerical model.
Based on the newly introduced definition of visibility, a set of experiments have been carried output in a purposed built smoke tunnel. Digital camera images of various illuminated signs were taken under different illumination, colour and smoke conditions. Using an algorithm developed by the author in this study, the digital camera images were converted into simulated human perceived images. The visibility of a target sign is measured against the quality of its image acquired. Conclusions have been drawn by comparing visibility under different conditions. One of them is that signs illuminated with red and green lights have the similar visibility that is far better than that with blue light. It is the first time this seemingly obvious conclusion has been quantified.
In the simulation of visibility in participating media, the author has introduced an algorithm that combines irradiance catching in 3D space with Monte Carlo ray tracing. It can calculate the distribution of scattered radiation with good accuracy without the high cost typically related to zonal method and the limitations in discrete ordinate method. The algorithm has been combined with a two pass solution method to produce high resolution images without introducing excessive number of rays from the light source. The convergence of the iterative solution procedure implemented has been theoretically proven. The accuracy of the model is demonstrated by comparing with the analytical solution of a point radiant source in 3D space. Further validation of the simulation model has been carried out by comparing the model prediction with the data from the smoke tunnel experiments.
The output of the simulation model has been presented in the form of an innovative floor map of visibility (FMV). It helps the fire safety designer to identify regions of poor visibility in a glance and will prove to be a very useful tool in performance based fire safety design
Image based analysis of visibility in smoke laden environments
This study investigates visibility in a smoke laden environment. For many years, researchers and engineers in fire safety have criticized the inadequacy of existing theory in describing the effects such as colour, viewing angle, environmental lighting etc. on the visibility of an emergency sign. In the current study, the author has raised the fundamental question on the concept of visibility and how it should be measured in fire safety engineering and tried to address the problem by redefining visibility based on the perceived image of a target sign. New algorithms have been created during this study to utilise modern hardware and software technology in the simulation of human perceived image of object in both experiment and computer modelling. Unlike the traditional threshold of visual distance, visibility in the current study has been defined as a continuous function changing from clearly discemable to completely invisible. It allows the comparison of visibility under various conditions, not just limited to the threshold. Current experiment has revealed that different conditions may results in the same visual threshold but follow very different path on the way leading to the threshold. The new definition of visibility has made the quantification of visibility in the pre-threshold conditions possible. Such quantification can help to improve the performance of fire evacuation since most evacuees will experience the pre-threshold condition. With current measurement of visibility, all the influential factors such as colour, viewing angle etc. can be tested in experiment and simulated in numerical model.Based on the newly introduced definition of visibility, a set of experiments have been carried output in a purposed built smoke tunnel. Digital camera images of various illuminated signs were taken under different illumination, colour and smoke conditions. Using an algorithm developed by the author in this study, the digital camera images were converted into simulated human perceived images. The visibility of a target sign is measured against the quality of its image acquired. Conclusions have been drawn by comparing visibility under different conditions. One of them is that signs illuminated with red and green lights have the similar visibility that is far better than that with blue light. It is the first time this seemingly obvious conclusion has been quantified.In the simulation of visibility in participating media, the author has introduced an algorithm that combines irradiance catching in 3D space with Monte Carlo ray tracing. It can calculate the distribution of scattered radiation with good accuracy without the high cost typically related to zonal method and the limitations in discrete ordinate method. The algorithm has been combined with a two pass solution method to produce high resolution images without introducing excessive number of rays from the light source. The convergence of the iterative solution procedure implemented has been theoretically proven. The accuracy of the model is demonstrated by comparing with the analytical solution of a point radiant source in 3D space. Further validation of the simulation model has been carried out by comparing the model prediction with the data from the smoke tunnel experiments.The output of the simulation model has been presented in the form of an innovative floor map of visibility (FMV). It helps the fire safety designer to identify regions of poor visibility in a glance and will prove to be a very useful tool in performance based fire safety design
Improvement of driver night vision in foggy environments by structured light projection
Nowadays, fog is still a natural phenomenon that hinders our ability to detect targets, particularly in the field of driving where accidents are increasing. In the literature we find different studies determining the range of visibility, improving the quality of an image, determining the characteristics of fog, etc. In this work we propose the possibility of using a structured lighting system, on which we project the light towards the target, limiting the field lighting. We have developed a scattering light propagation model to simulate and subsequently study the veil luminance, generated by backscattering, to predict the decrease in visibility. This simulation considers the type of fog, the relative orientation of various elements (observer, light source and targets).
We have built a fog chamber to validate the experimental params of the described system.
The results obtained from both the simulation and the experimental measurements demonstrate that it is possible to obtain a high contrast enhancement for viewing a target when illuminated as described.
Clearly, this kind of lighting technology will improve the road safety in foggy night environments. The results of this work can also be extrapolated to any situation in which the visibility of an observer is compromised by the environment, such as heavy rain, smoke from fires, among others
Characteristics of flight simulator visual systems
The physical parameters of the flight simulator visual system that characterize the system and determine its fidelity are identified and defined. The characteristics of visual simulation systems are discussed in terms of the basic categories of spatial, energy, and temporal properties corresponding to the three fundamental quantities of length, mass, and time. Each of these parameters are further addressed in relation to its effect, its appropriate units or descriptors, methods of measurement, and its use or importance to image quality
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