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Procedural Content Generation for Video Games using Open Data
Tuncel, Merve ; Gemrot, Jakub (advisor) ; Kratochvíl, Miroslav (referee)
Games get boring when they start repeating themselves and do not offer players new content. Procedural content generation (PCG) is increasingly used to generate this content. PCG-based game design decreases the need to have a human designer or a writer to generate the content. Algorithmic creation of game content can augment the creativity of human designers and this makes it possible small so-called indie teams to create the content for their game without the big resources. In this work, the field of PCG is introduced. Application of PCG is shown through a mobile game implementation. The implementation details of the mobile game Rush Hour will be presented that makes use of Foursquare, Twitter and Mapbox APIs, which eases the content creation using open data as the input of PCG.
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Implementation of a tone mapping operator for scotopic viewing conditions
Safko, Martin ; Wilkie, Alexander (advisor) ; Kratochvíl, Miroslav (referee)
Creating night-time images and movies that look plausible has been a problem in the industry since the creation of camera. To capture an image we need enough light to create a measurable quantity on a camera sensor. For this reason, shooting at night was not possible until sensors sensitive enough were developed and even then the captured images do not look realistic. Movie industry circumvent these issues by manually color correcting the footage in post-production. We implement an algorithm presented in a 2011 SIGGRAPH paper capable of solving this problem in a psycho-physically plausible and consistent way for spectral images and also augment it by a technique taken from a paper by INRIA. 1
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High-performance inverted index database
Javorský, Dávid ; Kratochvíl, Miroslav (advisor) ; Peška, Ladislav (referee)
The goal of this thesis is to implement an inverted-index database software that provides improvements in handling raw non-textual data, which is beneficial for several areas of research. The main internal structures of the library are designed to be cache-oblivious, also aiming to reduce the size of stored data. This thesis includes an overview of common inverted index implementation methods and describes retaled structures in a suitable cache-based model. This resulted in improvements of compression ratio, and performance similar to currently available highly optimized databases. The benchmark conducted on cheminformatic data has shown that the resulting software is applicable as an immediate, efficient replacement of the storage back-ends of specialized molecule databases.
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iOS emulator for Windows
Joneš, Jan ; Kratochvíl, Miroslav (advisor) ; Kofroň, Jan (referee)
The goal of this thesis is to create a program for Windows that takes a compiled iOS application and emulates it. However, only the application's machine code is emulated, whereas system functionality originally provided by iOS is translated to an equivalent functionality available on Windows. Hence, the emulated application employs a user interface and behavior that feel native on the target platform. At compile time, custom machine code is generated that supports the translation at runtime. The thesis also describes iOS's internals that the emulator needs to imitate and discusses different approaches to cross-platform development. 1
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Traffic sign classification by deep learning
Harmanec, Adam ; Blažek, Jan (advisor) ; Kratochvíl, Miroslav (referee)
Classification of road signs has been studied for many years and very promising results have been achieved. We present the analysis of used data sets as very limited for real case classification. In this thesis we analyse publicly available data sets and by merging and extending them, we create a wider and more comprehensive data set applicable in the Czech Republic. Finally, we propose a new convolutional neural network architecture and test it along with several preprocessing techniques on the new data set reaching accuracy of over 99%.
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OCR for tabular data
Tódová, Lucia ; Kratochvíl, Miroslav (advisor) ; Šefl, Vít (referee)
Table recognition is an important tool for digitalizing documents that con- tain tabular data, which often occur in areas of administration, finances and education. This thesis re-uses existing optical character recognition software to construct a new table recognition algorithm that aims to simplify the digitaliza- tion of diverse document types. The resulting algorithm achieves comparable or better results than currently available open-source software. Thesis additionally reviews common methods of OCR software implementation, and measures the influence of image preprocessing quality on the outcome of the table recognition. 1
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Accelerating structure search in small-molecule databases
Kratochvíl, Miroslav ; Bednárek, David (advisor) ; Hoksza, David (referee)
Structure search is one of the valuable capabilities of small-molecule databases. Available chemical cartridges typically provide acceptable search performance for processing user queries, but do not scale satisfactorily with dataset size. This thesis presents Sachem, a new open-source chemical car- tridge that implements a novel method of substructure search, which em- ploys newly designed fingerprints stored in inverted indexes. The perfor- mance of the method was assessed on datasets that contain tens of mil- lions of molecules. Comparison of the performance to that of other available cartridges revealed improvements in overall search speed, scaling potential and screen-out efficiency. Additionally, the thesis presents an application of Sachem; a SPARQL service that augments existing semantic services by including results of substructure and similarity searches in small-molecule databases. The result offers new possibilities for simpler querying of the interoperable heterogeneous data sources. 1
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Frege IDE with JetBrains MPS
Satmári, István ; Parízek, Pavel (advisor) ; Kratochvíl, Miroslav (referee)
Frege is an open-source project which brings the popular functional programming language Haskell to the Java ecosystem. JetBrains MPS is an open-source language workbench which allows users to design a new language and build an integrated development environment with a projectional (structured) editor for the created language. In this work we analyzed Frege grammar and created an IDE based on MPS that assists developers with writing code in the Frege language. Our environment includes a set of intuitive editors for editing Frege syntax, provides a simple type checking and implements code generators for the Frege language. Aim of the Frege IDE is its usability. Additionally, the thesis compares projectional editors with the more common plain-text IDEs, such as Eclipse, and evaluates whether they offer any advantage for editing purely functional programming languages.
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Adversarial examples generation for deep neural networks
Procházka, Štěpán ; Neruda, Roman (advisor) ; Kratochvíl, Miroslav (referee)
Machine learning models exhibit vulnerability to adversarial examples i.e., artificially created inputs that become misinterpreted. The goal of this work is to explore black-box adversarial attacks on deep networks performing image classification. The role of surrogate machine learning models for adversarial attacks is studied, and a special version of a genetic algorithm for generating adversarial examples is proposed. The efficiency of attacks is validated by a multitude of experiments with the Fashion MNIST data set. The experimental results verify the usability of our approach with surprisingly good performance in several cases, such as non-targeted attack on residual networks.
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Pattern recognition for in-game spell systems
Mikuš, Pavel ; Kratochvíl, Miroslav (advisor) ; Šefl, Vít (referee)
Magic is a popular element in current computer games. Although most games spoil the sensation of magic as of something extraordinarily subtle by allowing the player to cast spells by simply hitting key combinations, several games require the player to finish a more complicated action before casting a spell: Drawing a complicated glyph that represents the spell is one of such actions. This thesis aims to provide a repurposable library that would allow simple implementation of structured glyph-drawing-based in-game spell systems. The thesis studies several relevant approaches to pattern recognition, describes a neural-network based method for recognition of various shapes and shape combinations, develops a system for describing the parameters and results of the used algorithm in terms of predefined spell shapes and their recognized combinations, and implements this approach in a library and an accompanying simple demonstrational game. The library and its parameters are benchmarked and systematically optimized.
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