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M.J. Billeter
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1
Alternative Representations and Techniques for Accelerated Realistic Image Synthesis
Improved Sampling, Reconstruction and Modelling Methods
Realism has always been a major goal in visual content creation - from oil painting to motion pictures, from graphic arts to scientific data visualization. Computer graphics creates a virtual reality with digital representations. Trading between accuracy and speed, realistic rendering either creates photorealistic renders that follow strict rules of physics or approximates them with interactive alternatives.
The two approaches have their distinctive strengths and constraints. In this thesis, we focus on working from both ends towards realistic rendering. We study the highly accurate process of physically based rendering and introduce three novel methods dedicated to making it more efficient. We also investigate real-time depth of field rendering and develop a new model for an effect that is currently missing in state of the art systems.
Part i concerns sampling in numerical integration. Two methods are presented in Chapter 2 and Chapter 3. We first propose to perform path guiding in primary sample space, resulting in an effective and efficient scheme that is easy to plug into existing rendering pipelines. Secondly, we map visibility relations in a matrix-like table to steer the sampling process, which improves processes, such as visible light samples and light subpaths.
Part ii tackles the subsequent step after sampling in numerical integration. We present a new integration scheme in Chapter 4 that associates a weight to samples based on their adjacency, while remaining unbiased. The method delivers similar performance using uniform random samples as one can obtain with costly low-discrepancy sequences.
In Part iii this thesis revisits the optics behind depth of field effects and models distortion and shrinking effects that are missing in modern real-time rendering solutions. We are able to deliver similar effects to that of ray-traced results at a fraction of the cost.
Each chapter has detailed depiction and evaluation that helps readers better understand the methods and gain insights as to the applications thereof. ...
The two approaches have their distinctive strengths and constraints. In this thesis, we focus on working from both ends towards realistic rendering. We study the highly accurate process of physically based rendering and introduce three novel methods dedicated to making it more efficient. We also investigate real-time depth of field rendering and develop a new model for an effect that is currently missing in state of the art systems.
Part i concerns sampling in numerical integration. Two methods are presented in Chapter 2 and Chapter 3. We first propose to perform path guiding in primary sample space, resulting in an effective and efficient scheme that is easy to plug into existing rendering pipelines. Secondly, we map visibility relations in a matrix-like table to steer the sampling process, which improves processes, such as visible light samples and light subpaths.
Part ii tackles the subsequent step after sampling in numerical integration. We present a new integration scheme in Chapter 4 that associates a weight to samples based on their adjacency, while remaining unbiased. The method delivers similar performance using uniform random samples as one can obtain with costly low-discrepancy sequences.
In Part iii this thesis revisits the optics behind depth of field effects and models distortion and shrinking effects that are missing in modern real-time rendering solutions. We are able to deliver similar effects to that of ray-traced results at a fraction of the cost.
Each chapter has detailed depiction and evaluation that helps readers better understand the methods and gain insights as to the applications thereof. ...
Realism has always been a major goal in visual content creation - from oil painting to motion pictures, from graphic arts to scientific data visualization. Computer graphics creates a virtual reality with digital representations. Trading between accuracy and speed, realistic rendering either creates photorealistic renders that follow strict rules of physics or approximates them with interactive alternatives.
The two approaches have their distinctive strengths and constraints. In this thesis, we focus on working from both ends towards realistic rendering. We study the highly accurate process of physically based rendering and introduce three novel methods dedicated to making it more efficient. We also investigate real-time depth of field rendering and develop a new model for an effect that is currently missing in state of the art systems.
Part i concerns sampling in numerical integration. Two methods are presented in Chapter 2 and Chapter 3. We first propose to perform path guiding in primary sample space, resulting in an effective and efficient scheme that is easy to plug into existing rendering pipelines. Secondly, we map visibility relations in a matrix-like table to steer the sampling process, which improves processes, such as visible light samples and light subpaths.
Part ii tackles the subsequent step after sampling in numerical integration. We present a new integration scheme in Chapter 4 that associates a weight to samples based on their adjacency, while remaining unbiased. The method delivers similar performance using uniform random samples as one can obtain with costly low-discrepancy sequences.
In Part iii this thesis revisits the optics behind depth of field effects and models distortion and shrinking effects that are missing in modern real-time rendering solutions. We are able to deliver similar effects to that of ray-traced results at a fraction of the cost.
Each chapter has detailed depiction and evaluation that helps readers better understand the methods and gain insights as to the applications thereof.
The two approaches have their distinctive strengths and constraints. In this thesis, we focus on working from both ends towards realistic rendering. We study the highly accurate process of physically based rendering and introduce three novel methods dedicated to making it more efficient. We also investigate real-time depth of field rendering and develop a new model for an effect that is currently missing in state of the art systems.
Part i concerns sampling in numerical integration. Two methods are presented in Chapter 2 and Chapter 3. We first propose to perform path guiding in primary sample space, resulting in an effective and efficient scheme that is easy to plug into existing rendering pipelines. Secondly, we map visibility relations in a matrix-like table to steer the sampling process, which improves processes, such as visible light samples and light subpaths.
Part ii tackles the subsequent step after sampling in numerical integration. We present a new integration scheme in Chapter 4 that associates a weight to samples based on their adjacency, while remaining unbiased. The method delivers similar performance using uniform random samples as one can obtain with costly low-discrepancy sequences.
In Part iii this thesis revisits the optics behind depth of field effects and models distortion and shrinking effects that are missing in modern real-time rendering solutions. We are able to deliver similar effects to that of ray-traced results at a fraction of the cost.
Each chapter has detailed depiction and evaluation that helps readers better understand the methods and gain insights as to the applications thereof.
Master thesis
(2021)
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C.K.L. Man, P.J. Vardon, G. Remmerswaal, K.A. Hildebrandt, M.J. Billeter, Patricia Ammerlaan
To protect the Netherlands better from flooding, and with an eye on sea-level rise in the rest of the world, more accurate assessments are needed for dykes. The calculation for the most occurring failure mechanism in dykes, i.e. macro-instability, is limited by not being able to calculate large deformation when sliding occurs within a dyke. The random material point method (RMPM) is able to capture the complete failure path, including the residual dyke strength, while taking the heterogeneity of the soil into account, thereby improving the assessment of failure processes. However, as the method is not (yet) used in current practice, clear communication of the results is essential for convincing a wider public of the contribution of this method. Visuals are an important tool in communication, as it increases comprehension of the subject matter if the visual is designed efficiently. This research aims to investigate the available software and which techniques are suitable to make realistic and informative visualizations for a given RMPM dataset of slope failure problems.
A method to create visualization with a certain graphical realism in three-dimensional space is developed. The technique uses a computer graphic software (Blender) combined with an add-on, i.e. an extension plugin. The add-on allows to work with VTK software to process scientific data for visualization, thereby maintaining the scientific correctness of the visualizations. Moreover, a rendering pipeline in Blender is created, which transforms the properties from scientific colors into realistic materials, making the visualizations more intuitive.
However, the dataset is too large to summarize in a straightforward illustration. Therefore, a data analysis is obtained to classify each realization into five pre-defined failure profiles, which are determined based on a literature study. Four failure profiles are classified based on the number of retrogressive failures and whether or not the realization resulted in flooding, while the fifth class describes horizontal failures. A technique has been developed to separate the horizontal failures from the other classes based on the plastic deviatoric strain attribute. Additionally, the data analysis aims to characterize the behavior of each failure profile from an early start, such that the findings could be used for current methods, which could not calculate the full failure profile.
Therefore, this thesis needs to investigate the reduction of the dataset to make it more time efficient when doing a data analysis. It is extended on the clustering algorithm, which has the function to detect failure blocks based on the displacement per dyke profile. The reduction method replaces an amount of data by one representative point per cluster. It not only reduced the size of the dataset significantly, from 3000 GB to 6 GB, it also made the comparison of attributes between realizations, and therefore the data analysis, easier.
The data analysis shows that it is hard to distinguish different failure profiles using only data of the initial failure, which shows the importance of using RMPM to account for post-failure behavior instead of using the current assessment i.e. FEM and LEM. One finding is that equilibrium of the initial failure block is often reached before a vertical crest displacement equal to 0.5 times the height of the dyke. This indicates that the crude estimation in the current assessment is highly conservative. Moreover, within the assumption, it is hypothesized that the secondary failure block will only form after the initial failure block has reached its equilibrium, which is shown otherwise within the data analysis of this thesis.
This work proposes a method for data analysis of RMPM using parallel coordinates, which can be extended to other RMPM datasets for macro-instability and can help to improve the prediction of the probability of flooding. Moreover, it proposes a method to visualize the prominent features, determined using parallel coordinates, in Blender-VTK. This work can, in future research, be extended to other geotechnical problems, such as 3-dimensional dyke slope failure.
...
A method to create visualization with a certain graphical realism in three-dimensional space is developed. The technique uses a computer graphic software (Blender) combined with an add-on, i.e. an extension plugin. The add-on allows to work with VTK software to process scientific data for visualization, thereby maintaining the scientific correctness of the visualizations. Moreover, a rendering pipeline in Blender is created, which transforms the properties from scientific colors into realistic materials, making the visualizations more intuitive.
However, the dataset is too large to summarize in a straightforward illustration. Therefore, a data analysis is obtained to classify each realization into five pre-defined failure profiles, which are determined based on a literature study. Four failure profiles are classified based on the number of retrogressive failures and whether or not the realization resulted in flooding, while the fifth class describes horizontal failures. A technique has been developed to separate the horizontal failures from the other classes based on the plastic deviatoric strain attribute. Additionally, the data analysis aims to characterize the behavior of each failure profile from an early start, such that the findings could be used for current methods, which could not calculate the full failure profile.
Therefore, this thesis needs to investigate the reduction of the dataset to make it more time efficient when doing a data analysis. It is extended on the clustering algorithm, which has the function to detect failure blocks based on the displacement per dyke profile. The reduction method replaces an amount of data by one representative point per cluster. It not only reduced the size of the dataset significantly, from 3000 GB to 6 GB, it also made the comparison of attributes between realizations, and therefore the data analysis, easier.
The data analysis shows that it is hard to distinguish different failure profiles using only data of the initial failure, which shows the importance of using RMPM to account for post-failure behavior instead of using the current assessment i.e. FEM and LEM. One finding is that equilibrium of the initial failure block is often reached before a vertical crest displacement equal to 0.5 times the height of the dyke. This indicates that the crude estimation in the current assessment is highly conservative. Moreover, within the assumption, it is hypothesized that the secondary failure block will only form after the initial failure block has reached its equilibrium, which is shown otherwise within the data analysis of this thesis.
This work proposes a method for data analysis of RMPM using parallel coordinates, which can be extended to other RMPM datasets for macro-instability and can help to improve the prediction of the probability of flooding. Moreover, it proposes a method to visualize the prominent features, determined using parallel coordinates, in Blender-VTK. This work can, in future research, be extended to other geotechnical problems, such as 3-dimensional dyke slope failure.
...
To protect the Netherlands better from flooding, and with an eye on sea-level rise in the rest of the world, more accurate assessments are needed for dykes. The calculation for the most occurring failure mechanism in dykes, i.e. macro-instability, is limited by not being able to calculate large deformation when sliding occurs within a dyke. The random material point method (RMPM) is able to capture the complete failure path, including the residual dyke strength, while taking the heterogeneity of the soil into account, thereby improving the assessment of failure processes. However, as the method is not (yet) used in current practice, clear communication of the results is essential for convincing a wider public of the contribution of this method. Visuals are an important tool in communication, as it increases comprehension of the subject matter if the visual is designed efficiently. This research aims to investigate the available software and which techniques are suitable to make realistic and informative visualizations for a given RMPM dataset of slope failure problems.
A method to create visualization with a certain graphical realism in three-dimensional space is developed. The technique uses a computer graphic software (Blender) combined with an add-on, i.e. an extension plugin. The add-on allows to work with VTK software to process scientific data for visualization, thereby maintaining the scientific correctness of the visualizations. Moreover, a rendering pipeline in Blender is created, which transforms the properties from scientific colors into realistic materials, making the visualizations more intuitive.
However, the dataset is too large to summarize in a straightforward illustration. Therefore, a data analysis is obtained to classify each realization into five pre-defined failure profiles, which are determined based on a literature study. Four failure profiles are classified based on the number of retrogressive failures and whether or not the realization resulted in flooding, while the fifth class describes horizontal failures. A technique has been developed to separate the horizontal failures from the other classes based on the plastic deviatoric strain attribute. Additionally, the data analysis aims to characterize the behavior of each failure profile from an early start, such that the findings could be used for current methods, which could not calculate the full failure profile.
Therefore, this thesis needs to investigate the reduction of the dataset to make it more time efficient when doing a data analysis. It is extended on the clustering algorithm, which has the function to detect failure blocks based on the displacement per dyke profile. The reduction method replaces an amount of data by one representative point per cluster. It not only reduced the size of the dataset significantly, from 3000 GB to 6 GB, it also made the comparison of attributes between realizations, and therefore the data analysis, easier.
The data analysis shows that it is hard to distinguish different failure profiles using only data of the initial failure, which shows the importance of using RMPM to account for post-failure behavior instead of using the current assessment i.e. FEM and LEM. One finding is that equilibrium of the initial failure block is often reached before a vertical crest displacement equal to 0.5 times the height of the dyke. This indicates that the crude estimation in the current assessment is highly conservative. Moreover, within the assumption, it is hypothesized that the secondary failure block will only form after the initial failure block has reached its equilibrium, which is shown otherwise within the data analysis of this thesis.
This work proposes a method for data analysis of RMPM using parallel coordinates, which can be extended to other RMPM datasets for macro-instability and can help to improve the prediction of the probability of flooding. Moreover, it proposes a method to visualize the prominent features, determined using parallel coordinates, in Blender-VTK. This work can, in future research, be extended to other geotechnical problems, such as 3-dimensional dyke slope failure.
A method to create visualization with a certain graphical realism in three-dimensional space is developed. The technique uses a computer graphic software (Blender) combined with an add-on, i.e. an extension plugin. The add-on allows to work with VTK software to process scientific data for visualization, thereby maintaining the scientific correctness of the visualizations. Moreover, a rendering pipeline in Blender is created, which transforms the properties from scientific colors into realistic materials, making the visualizations more intuitive.
However, the dataset is too large to summarize in a straightforward illustration. Therefore, a data analysis is obtained to classify each realization into five pre-defined failure profiles, which are determined based on a literature study. Four failure profiles are classified based on the number of retrogressive failures and whether or not the realization resulted in flooding, while the fifth class describes horizontal failures. A technique has been developed to separate the horizontal failures from the other classes based on the plastic deviatoric strain attribute. Additionally, the data analysis aims to characterize the behavior of each failure profile from an early start, such that the findings could be used for current methods, which could not calculate the full failure profile.
Therefore, this thesis needs to investigate the reduction of the dataset to make it more time efficient when doing a data analysis. It is extended on the clustering algorithm, which has the function to detect failure blocks based on the displacement per dyke profile. The reduction method replaces an amount of data by one representative point per cluster. It not only reduced the size of the dataset significantly, from 3000 GB to 6 GB, it also made the comparison of attributes between realizations, and therefore the data analysis, easier.
The data analysis shows that it is hard to distinguish different failure profiles using only data of the initial failure, which shows the importance of using RMPM to account for post-failure behavior instead of using the current assessment i.e. FEM and LEM. One finding is that equilibrium of the initial failure block is often reached before a vertical crest displacement equal to 0.5 times the height of the dyke. This indicates that the crude estimation in the current assessment is highly conservative. Moreover, within the assumption, it is hypothesized that the secondary failure block will only form after the initial failure block has reached its equilibrium, which is shown otherwise within the data analysis of this thesis.
This work proposes a method for data analysis of RMPM using parallel coordinates, which can be extended to other RMPM datasets for macro-instability and can help to improve the prediction of the probability of flooding. Moreover, it proposes a method to visualize the prominent features, determined using parallel coordinates, in Blender-VTK. This work can, in future research, be extended to other geotechnical problems, such as 3-dimensional dyke slope failure.
Master thesis
(2021)
-
Z. Jia, R. Guerra Marroquim, M.J. Billeter, E. Eisemann, A.J.L. Adam, S.E. Verwer
Suppose we have a target radiance distribution, a light source, and a plane for receiving light. How do we design a reflector that can give a similar result as the target radiance distribution? The inverse reflector problem is of high interest for light designers and related industries, such as lamp manufacture, headlight and street light design, and interior designs. There have been some researches on this specific topic. Nevertheless, the existing algorithms are either not fully compatible with parallel acceleration or have a narrow application scope (can only handle the far-field problem). This thesis's goal is to design a method that can have a fast approximation of the inverse reflector problem and handle different application scenarios. The core of the proposed method in this thesis is a modified simulated annealing algorithm. I first give the definition of the inverse reflector problem and explain why I choose simulated annealing in the proposed method by analysing the related works and various optimisation algorithms. Then, I detail what issues the plain simulated annealing algorithm will have and why it cannot achieve satisfactory results. Moreover, to solve the issues and improve performance, I propose additional strategies, such as Phong tessellation, randomisation strategy, multi-level strategy, history-decision strategy and penalising strategy. I also discuss the system design based on the proposed method and how to accelerate the optimisation process in this system. I evaluate and validate the proposed method by running test cases in different scenarios and compare the results with other algorithms. The results show that the method, as a general optimisation algorithm, can achieve good results in different application scenarios. The compatibility, speed and accuracy are the main advantages. The result of the proposed method can also serve as the initial guess for a finer optimisation.
...
Suppose we have a target radiance distribution, a light source, and a plane for receiving light. How do we design a reflector that can give a similar result as the target radiance distribution? The inverse reflector problem is of high interest for light designers and related industries, such as lamp manufacture, headlight and street light design, and interior designs. There have been some researches on this specific topic. Nevertheless, the existing algorithms are either not fully compatible with parallel acceleration or have a narrow application scope (can only handle the far-field problem). This thesis's goal is to design a method that can have a fast approximation of the inverse reflector problem and handle different application scenarios. The core of the proposed method in this thesis is a modified simulated annealing algorithm. I first give the definition of the inverse reflector problem and explain why I choose simulated annealing in the proposed method by analysing the related works and various optimisation algorithms. Then, I detail what issues the plain simulated annealing algorithm will have and why it cannot achieve satisfactory results. Moreover, to solve the issues and improve performance, I propose additional strategies, such as Phong tessellation, randomisation strategy, multi-level strategy, history-decision strategy and penalising strategy. I also discuss the system design based on the proposed method and how to accelerate the optimisation process in this system. I evaluate and validate the proposed method by running test cases in different scenarios and compare the results with other algorithms. The results show that the method, as a general optimisation algorithm, can achieve good results in different application scenarios. The compatibility, speed and accuracy are the main advantages. The result of the proposed method can also serve as the initial guess for a finer optimisation.
Measurement Light Bulb
Control
Bachelor thesis
(2019)
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Rob Damsteegt, Jippe van Dunné, Elmar Eisemann, Markus Billeter, Ioan Lager, David Elkouss Coronas
This document describes the design process the prototype of a measurement light bulb which is able to project spherical harmonics of orders 0-1-2. Photographs of these projections can be combined to represent many light distributions. The measurement light bulb can be used in the field of research focused on the computation of the illumination impact of lighting, more specifically, simulating different light sources. Our prototype consists of a laser beam rotating over two axes, which allows the device to project onto a sphere around itself. The device can be controlled wirelessly using Bluetooth. The lamp can project spherical harmonics in a resolution of 4 degree and 256 monochrome light levels. The time one projection takes is about one second, which allows for quick measurements. The dimensions and the weight of the lamp are such that it is portable. At this stage, the prototype can only operate in a dark environment, due to the use of a low powered laser. In this document, the focus will be on the design of control, communication and the PCB.
...
This document describes the design process the prototype of a measurement light bulb which is able to project spherical harmonics of orders 0-1-2. Photographs of these projections can be combined to represent many light distributions. The measurement light bulb can be used in the field of research focused on the computation of the illumination impact of lighting, more specifically, simulating different light sources. Our prototype consists of a laser beam rotating over two axes, which allows the device to project onto a sphere around itself. The device can be controlled wirelessly using Bluetooth. The lamp can project spherical harmonics in a resolution of 4 degree and 256 monochrome light levels. The time one projection takes is about one second, which allows for quick measurements. The dimensions and the weight of the lamp are such that it is portable. At this stage, the prototype can only operate in a dark environment, due to the use of a low powered laser. In this document, the focus will be on the design of control, communication and the PCB.