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Texture-Based Object Recognition
Wozniak, Jan ; Hradiš, Michal (referee) ; Španěl, Michal (advisor)
This thesis is focused on analysis of texture-based features and classi cation of known objects. The technical report provides basic outline of commonly used texture features and principles of their classifi cation, whereas narrower attention is dedicated to extraction of Local Binary Patterns and Support Vector Machine algorithm based classi er. This work also includes evaluation of attained results by statistical methods Jackkni ng and F-measure.
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Moving Objects Indexing
Vetešník, Jiří ; Chmelař, Petr (referee) ; Zendulka, Jaroslav (advisor)
This work is aimed for proposing acceptable indexing of moving objects. With the enlargement of mobile computing it is needed to manage large sets of spatiotemporal data. We introduce the problem of spatiotemporal data and basic general approaches of indexing these data. Further, we show support of spatial data in Oracle. The movement is typically represented as trajectory in two dimensional space with temporal component in third dimension. The thesis contains experiments performed in database Oracle on artificially generate data.
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3D Spatial Indexing of Objects
Drbal, Miroslav ; Dvořák, Radim (referee) ; Orság, Filip (advisor)
This diploma thesis defines the term indexing and in preamble are discussed known indexing algorithms and difference between indexing static and moving objects. The practical part of this diploma thesis is aimed to designing and implementing of indexing algorithm for open source application MaNGOS with respect to generic design pattern and effectiveness of spatial search queries for selection of the objects given properties in the specified area. At the end I present and discuss reached results.
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Texture-Based Object Recognition
Wozniak, Jan ; Hradiš, Michal (referee) ; Španěl, Michal (advisor)
This thesis is focused on analysis of texture-based features and classi cation of known objects. The technical report provides basic outline of commonly used texture features and principles of their classifi cation, whereas narrower attention is dedicated to extraction of Local Binary Patterns and Support Vector Machine algorithm based classi er. This work also includes evaluation of attained results by statistical methods Jackkni ng and F-measure.
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Moving Objects Indexing
Křížová, Martina ; Ráb, Jaroslav (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with indexing of spatio-temporal data. It describes existing approaches to indexing data and support for indexing in Oracle Database 11g. The aim of this work is to design structures of databases for storing spatio-temporal data over Oracle Database 11g to propose experiments for these databases. Ways of spatio-temporal data storage are evaluated according to these experiments in terms of time demands of queries and appropriateness of using available indexing structure and spatial operators.
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3D Spatial Indexing of Objects
Drbal, Miroslav ; Dvořák, Radim (referee) ; Orság, Filip (advisor)
This diploma thesis defines the term indexing and in preamble are discussed known indexing algorithms and difference between indexing static and moving objects. The practical part of this diploma thesis is aimed to designing and implementing of indexing algorithm for open source application MaNGOS with respect to generic design pattern and effectiveness of spatial search queries for selection of the objects given properties in the specified area. At the end I present and discuss reached results.
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Moving Objects Indexing
Vetešník, Jiří ; Chmelař, Petr (referee) ; Zendulka, Jaroslav (advisor)
This work is aimed for proposing acceptable indexing of moving objects. With the enlargement of mobile computing it is needed to manage large sets of spatiotemporal data. We introduce the problem of spatiotemporal data and basic general approaches of indexing these data. Further, we show support of spatial data in Oracle. The movement is typically represented as trajectory in two dimensional space with temporal component in third dimension. The thesis contains experiments performed in database Oracle on artificially generate data.
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