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Distributed Ray Tracing in Reasonable Time
Slovák, Radek ; Polok, Lukáš (referee) ; Herout, Adam (advisor)
This thesis deals with the method of distributed ray tracing focusing on optimalization of this method. The method uses simulation of some attributes of light by distributing rays of lights and it produces high quality and partly realistic images. The price for realitic effects is the high computational complexity of the method. The thesis analysis the theory connected with these aspects. A large part describes optimalizations of this method, i.e. searching for the nearest triangle intersection using kd-trees, quasi random sampling with faster convergence, the use of SSE instruction set and fast ray - triangle intersection. These optimalizations brought a noticable speed - up. The thesis includes description of implementation of these techniques. The implementation itself emphasises the practical usability including generating some advanced animations and universal description of objects.
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Sketching 3D Models
David, Tomáš ; Hulík, Rostislav (referee) ; Kršek, Přemysl (advisor)
This thesis deals with the processing and representation of polygonal models. It is devoted to methods for creating and editing 3D models, especially the sketching method. It describes the procedure for design and implementation of a simple plug-in for application OpenFlipper. This plug-in allows creation of 3D model of object by drawing a closed line.
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Surface Reconstruction from Point Clouds
Jarůšek, Tomáš ; Zemčík, Pavel (referee) ; Španěl, Michal (advisor)
Surface reconstruction from point clouds represents very modern and widespreadly used method for digitalization of real surfaces. The main focus of this work is on a comparison of several algorithms (Poisson surface reconstruction, Ball Pivoting Algorithm, Fourier surface reconstruction, Wavelet surface reconstruction and Multi-level Partition of Unity implicits) that reconstruct original surface in a form of triangle mesh from an oriented point cloud. Every algorithm was used in a series of tests on both real and synthetic datasets which were also modified to suit more complicated experiments. The following evaluation is done in various categories. The results are evaluated both visualy and with calculated measures (such as Hausdorff distance). Together these experiments depict a detailed analysis of the state of surface reconstruction algorithms. Our experimets show that the selection of optimal algorithm depends on a concrete task. Overall Possion surface reconstruction and Fourier surface reconstruction provide the best results.
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Symmetry of triangle meshes
Vévoda, Petr ; Pelikán, Josef (advisor) ; Krajíček, Václav (referee)
Triangle meshes belong to methods of storing a surface of a threedimensional object in computer memory. A human face can be represented this way too. Findings about symmetry of faces are valuable for a variety of fields of study such as anthropology, medicine, criminalistics or psychology. For computing an approximate plane of symmetry of a face we have proposed an algorithm based on a gradient method, which minimizes distance between its mesh and its symmetric image over a set of all planes. However, it is possible to apply this algorithm to an arbitrary mesh and use its landmarks too. We have integrated the implementation covering also results visualization into Morphome3cs project focused on computations in anthropology.
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Surface registrations for topology transfer in geometric morphometry
Dupej, Ján ; Pelikán, Josef (advisor) ; Telea, Alexandru C. (referee) ; Váša, Libor (referee)
Geometric morphometry serves biologists and anthropologists to rigorously and quantitatively describe shapes. These representations can be treated as a statistical sample, allowing the researchers to study its variability within groups and correlate it to other features. Geometric morphometry uses landmarks as the proxy for shape, with consistent semantics in each specimen. General triangle meshes do not have this property, and as such, semantically consistent remeshes must be created artificially. This thesis deals with the design of an algorithm that consistently resamples a set of surface models for the purpose of statistical analysis. Coherent point drift was employed to perform nonrigid registration, whose result is then used to generate a semantically consistent remeshes. This approach was successfully applied in a number of studies. As CPD is compute-intensive, we propose methods of accelerating both its initialization and processing phases. Also, an extension was introduced, that can map the deviation of the surfaces from perfect bilateral symmetry and analyze it in a sample, which is significant, among others, for quantification of pathologies. Manual trimming of the surfaces and merging datasets results in outlier regions in the individual surfaces and potentially large differences in their vertex...
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Statistical model of the face shape
Boková, Kateřina ; Pelikán, Josef (advisor) ; Krajíček, Václav (referee)
The goal of this thesis is to use machine learning methods for datasets of scanned faces and to create a program that allows to explore and edit faces represented as triangle meshes with a number of controls. Firstly we had to reduce dimension of triangle meshes by PCA and then we tried to predict shape of meshes according to physical properties like weight, height, age and BMI. The modeled faces can be used in animation or games.
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Statistical model of the face shape
Boková, Kateřina ; Pelikán, Josef (advisor) ; Krajíček, Václav (referee)
The goal of this thesis is to use machine learning methods for datasets of scanned faces and to create a program that allows to explore and edit faces represented as triangle meshes with a number of controls. Firstly we had to reduce dimension of triangle meshes by PCA and then we tried to predict shape of meshes according to physical properties like weight, height, age and BMI. The modeled faces can be used in animation or games.
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Using DNN for triangular network analysis in geometric morphometry
Dvořáková, Gabriela ; Pelikán, Josef (advisor) ; Dupej, Ján (referee)
The aim of this thesis is to use deep learning for the task of 3D object recognition. Deep learning has been succesfully used for three dimensional data recognition. However, most of the published work chose to represent 3D objects as a set of projected 2D pixel images or in the form of binary voxels. The main goal is to propose an alternative mapping of 3D data to the NN input. Three data representations are introduced: Treating vertex coordinates as a 1D array, projection to a 2D grid and a set of surface oblique lines crossing the sig- nificant parts of an object. All of the proposed data representations are tested for the gender classification task using NN and CNN on 3D facial models. We analyzed the impact of coordinate relativization and a new modified dataset crea- ted by extracting a nose area from original triangle meshes. Experimental results confirmed the quality of the oblique lines approach with achieved classification accuracies of 84, 2% using CNN. 1
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Visualization of the difference between two triangle meshes
Horešovský, Jan ; Pelikán, Josef (advisor) ; Dupej, Ján (referee)
Visualization of the difference between two triangle meshes is useful in geometric morphometrics where the shapes of biological objects such as bones, facial symme- tries and others are studied. Existing visualizations are mostly done by encoding various difference metrics into vertex color. However, this one-dimensional infor- mation is not enough to display multiple metrics at the same time. To overcome this limitation, we implemented an algorithm which employs the techniques of vector field visualization and uses clustered 3D arrows to encode the metrics. Focusing on visual appearance, we applied it in several types of visualizations in an experimental application called MeshDiff. We also conducted a user study of both existing and new visualizations to compare their performance in various use cases and investigate the possibilities for future improvement. 1
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