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Procedural modeling and realism in computer graphics
Beneš, Jan ; Křivánek, Jaroslav (advisor)
One of the long-standing goals of computer graphics is to generate realistic imagery. This realism is predicated, among other things, on having access to high- quality content to display, and being able to verify its realism. Unfortunately, realism and especially realism in procedural modeling are under-represented in current literature. Consequently, we address these two topics by investigating the definitions of general realism in computer graphics and by providing a basic framework for thinking and talking about realism in procedural modeling. In or- der to provide this framework with initial tangible data, we present a user study of the realism of procedural buildings. We find that realism of this specific class of procedural models is carried on different scales and conclude that authors of procedural rules for buildings need to beware of not only the fine details, but also the overall shape of the generated models. Finally, we present a method for growing procedural road networks in and close to cities. We use a traffic simula- tion and adapt existing research to grow cities over time. The cities are formed by letting several meaningfully positioned smaller settlements' minor roads grow in step with additional major roads. As a result, we are able to generate cities with rich, complex and realistic...
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Procedural modeling and realism in computer graphics
Beneš, Jan ; Křivánek, Jaroslav (advisor)
One of the long-standing goals of computer graphics is to generate realistic imagery. This realism is predicated, among other things, on having access to high- quality content to display, and being able to verify its realism. Unfortunately, realism and especially realism in procedural modeling are under-represented in current literature. Consequently, we address these two topics by investigating the definitions of general realism in computer graphics and by providing a basic framework for thinking and talking about realism in procedural modeling. In or- der to provide this framework with initial tangible data, we present a user study of the realism of procedural buildings. We find that realism of this specific class of procedural models is carried on different scales and conclude that authors of procedural rules for buildings need to beware of not only the fine details, but also the overall shape of the generated models. Finally, we present a method for growing procedural road networks in and close to cities. We use a traffic simula- tion and adapt existing research to grow cities over time. The cities are formed by letting several meaningfully positioned smaller settlements' minor roads grow in step with additional major roads. As a result, we are able to generate cities with rich, complex and realistic...
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Procedural modeling and realism in computer graphics
Beneš, Jan ; Křivánek, Jaroslav (advisor) ; Patow, Gustavo (referee) ; Biljecki, Filip (referee)
One of the long-standing goals of computer graphics is to generate realistic imagery. This realism is predicated, among other things, on having access to high- quality content to display, and being able to verify its realism. Unfortunately, realism and especially realism in procedural modeling are under-represented in current literature. Consequently, we address these two topics by investigating the definitions of general realism in computer graphics and by providing a basic framework for thinking and talking about realism in procedural modeling. In or- der to provide this framework with initial tangible data, we present a user study of the realism of procedural buildings. We find that realism of this specific class of procedural models is carried on different scales and conclude that authors of procedural rules for buildings need to beware of not only the fine details, but also the overall shape of the generated models. Finally, we present a method for growing procedural road networks in and close to cities. We use a traffic simula- tion and adapt existing research to grow cities over time. The cities are formed by letting several meaningfully positioned smaller settlements' minor roads grow in step with additional major roads. As a result, we are able to generate cities with rich, complex and realistic...
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Procedural generation of pencil drawings
Studna, Martin ; Křivánek, Jaroslav (advisor) ; Nindel, Thomas Klaus (referee)
The aim of the thesis is to implement a procedural method which transfers a natural image into a pencil drawing-like style. Our project is written in C++. It uses libraries like OpenCV for image processing and Eigen for linear algebra computations. Since neural networks are frequently questioned, as to whether or not they are better than procedural methods for artistic style reproduction, this work presents also a detailed comparison of both of these approaches. We have re-implemented a selected method for procedural generation of pencil drawing style, bringing several modifications. We compare results of the method with a recently released code for neural network-based drawing generation. The result of this subjective comparison indicates that neural networks maybe be better suited for the generation of pencil-like hatching texture to reproduce shading. On the other hand, the procedurally generated outlined produced by the implemented approach provide more natural renderings.
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Dimensional measurements from a limited set of X-ray projections
Iser, Tomáš ; Horáček, Jan (advisor) ; Křivánek, Jaroslav (referee)
Modern non-destructive approaches for quality control in manufacturing often rely on X-ray computed tomography to measure even difficult-to-reach features. Unfortunately, such measurements require hundreds or thousands of calibrated X-ray projections, which is a time-consuming process and may cause bottlenecks. In the recent state-of-the-art research, tens and hundreds of projections are still required. In this thesis, we examine the radiography physics, technologies, and ex- isting solutions, and we propose a novel approach for non-destructive dimensional measurements from a limited number of projections. Instead of relying on com- puted tomography, we formulate the measurements as a minimization problem in which we compare our parametric model to reference radiographs. We propose the whole dimensional measurements pipeline, including object parametrizations, material calibrations, simulations, and hierarchical optimizations. We fully im- plemented the method and evaluated its accuracy and repeatability using real radiographs of real physical objects. We achieved accuracy in the range of tens or hundreds of micrometers, which is almost comparable to industrial computed tomography, but we only used two or three reference radiographs. These results are significant for industrial quality control. Acquiring...
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Using neural networks to generate realistic skies
Hojdar, Štěpán ; Křivánek, Jaroslav (advisor) ; Šikudová, Elena (referee)
Environment maps are widely used in several computer graphics fields, such as realistic architectural rendering or computer games as sources of the light in the scene. Obtaining these maps is not easy, since they have to have both a high- dynamic range as well as a high resolution. As a result, they are expensive to make and the supply is limited. Deep neural networks are a widely unexplored research area and have been successfully used for generating complex and realistic images like human portraits. Neural networks perform well at predicting data from complex models, which are easily observable, such as photos of the real world. This thesis explores the idea of generating physically plausible environment maps by utilizing deep neural networks known as generative adversarial networks. Since a skydome dataset is not publicly available, we develop a scalable capture process with both low-end and high-end hardware. We implement a pipeline to process the captured data before feeding it to a network and extend an already existing network architecture to generate HDR environment maps. We then run a series of experiments to determine the quality of the results and uncover the directions of possible further research.
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3D object classification using neural networks
Krabec, Miroslav ; Křivánek, Jaroslav (advisor) ; Šikudová, Elena (referee)
3D Object Classification Using Neural Networks Bc. Miroslav Krabec Classification of 3D objects is of great interest in the field of artificial intelligence. There are numerous approaches using artificial neural networks to address this problem. They differ mainly in the representation of the 3D model used as input and the network architecture. The goal of this thesis is to explore and test these approaches on publicly available datasets and subject them to independent comparison, which has not so far appeared in the literature. We provide a unified framework allowing to convert the data from common 3D formats. We train and test ten different network on the ModelNet40 and ShapeNetCore datasets. All the networks performed reasonably well in our tests, but we were generally unable to achieve the accuracies reported in the original papers. We suspect this could be due to extensive, albeit unreported, hyperparameter tuning by the authors of the original papers, suggesting this issue would benefit from further research. 1
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Global exploration in Markov chain Monte Carlo methods for light transport simulation
Šik, Martin ; Křivánek, Jaroslav (advisor) ; Jakob, Wenzel (referee) ; Christensen, Per (referee)
Monte Carlo light transport simulation has become a de-facto standard tool for photorealistic rendering. However, the algorithms used by the current rendering systems are often ineffective, especially in scenes featuring light transport due to multiple highly glossy or specular interactions and complex visibility between the camera and light sources. It is therefore desirable to adopt more robust algorithms in practice. Light transport algorithms based on Markov chain Monte Carlo (MCMC) are known to be effective at sampling many different kinds of light transport paths even in the presence of complex visibility. However, the current MCMC algorithms often over-sample some of the paths while under-sampling or completely missing other paths. We attribute this behavior to insufficient global exploration of path space which leads to their unpredictable convergence and causes the occurrence of image artifacts. This in turn prohibits adoption of MCMC algorithms in practice. In this thesis we therefore focus on improving global exploration in MCMC algorithms for light transport simulation. First, we present a new MCMC algorithm that utilizes replica exchange to improve global exploration. To maximize efficiency of replica exchange we introduce tempering of the path space, which allows easier discovery of important...
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Evaluation of Dynamic Range Reconstruction Approaches and a Mobile Application for HDR Photo Capture
Mirbauer, Martin ; Křivánek, Jaroslav (advisor) ; Šikudová, Elena (referee)
Digital photography became widespread with the global use of smartphones. However, most of the captured images do not fully use the camera capabilities by storing the captured photos in a format with limited dynamic range. The subject of dynamic range expansion and reconstruction has been researched since early 2000s and recently gave rise to several new reconstruction methods using convolutional neural networks (CNNs), whose performance has not yet been comprehensively compared. By implementing and using our dynamic range reconstruction evaluation framework we compare the reconstruction quality of individual CNN-based approaches. We also implement a mobile HDR camera application and evaluate the feasibility of running the best-performing reconstruction method directly on a mobile device.
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Efficient rendering of fine structures on object surfaces
Brečka, Bohuš ; Křivánek, Jaroslav (advisor) ; Kondapaneni, Ivo (referee)
Current methods for realistic rendering approximate surface microstructure using a smooth normal distribution function. This approach is not sufficient for the rendering of shiny surfaces with details (such as scratches) visible under bright light in real world. It is possible to model surface structure with high-resolution normal maps, but this approach leads to unreasonable rendering times when used with modern rendering methods based on stochastic sampling. In this thesis, we explore some of the approaches specifically designed to address this problem. As a main topic we choose the algorithm proposed by Yen et al. [2016]. We analyse, implement it, compare it with other approaches and propose some improvements. As a part of this work we implement a rendering system based on the path tracing algorithm, which is used as an environment for testing and visualization of our results.
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