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Knowledge Discovery in Multimedia Databases
Málik, Peter ; Bartík, Vladimír (referee) ; Chmelař, Petr (advisor)
This master"s thesis deals with the knowledge discovery in multimedia databases. It contains general principles of knowledge discovery in databases, especially methods of cluster analysis used for data mining in large and multidimensional databases are described here. The next chapter contains introduction to multimedia databases, focusing on the extraction of low level features from images and video data. The practical part is then an implementation of the methods BIRCH, DBSCAN and k-means for cluster analysis. Final part is dedicated to experiments above TRECVid 2008 dataset and description of achievements.
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Knowledge Discovery in Image Databases
Jaroš, Ondřej ; Řezníček, Ivo (referee) ; Chmelař, Petr (advisor)
This thesis is focused on knowledge discovery from databases, especially on methods of classification and prediction. These methods are described in detail. Furthermore, this work deals with multimedia databases and the way these databases store data. In particular, the method for processing low-level image and video data is described. The practical part of the thesis focuses on the implementation of this GMM method used for extracting low-level features of video data and images. In other parts, input data and tools, which the implemented method was compared with, are described. The last section focuses on experiments comparing extraction efficiency features of high-level attributes of low-level data and the methods implemented in selected classification tools LibSVM.
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Multimodal Database Search
Krejčíř, Tomáš ; Stryka, Lukáš (referee) ; Chmelař, Petr (advisor)
The field that deals with storing and effective searching of multimedia documents is called Information retrieval. This paper describes solution of effective searching in collections of shots. Multimedia documents are presented as vectors in high-dimensional space, because in such collection of documents it is easier to define semantics as well as the mechanisms of searching. The work aims at problems of similarity searching based on metric space, which uses distance functions, such as Euclidean, Chebyshev or Mahalanobis, for comparing global features and cosine or binary rating for comparing local features. Experiments on the TRECVid dataset compare implemented distance functions. Best distance function for global features appears to be Mahalanobis and for local features cosine rating.
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Knowledge Discovery in Multimedia Databases
Jirmásek, Tomáš ; Řezníček, Ivo (referee) ; Chmelař, Petr (advisor)
This master's thesis deals with knowledge discovery in databases, especially basic methods of classification and prediction used for data mining are described here. The next chapter contains introduction to multimedia databases and knowledge discovery in multimedia databases. The main goal of this chapter was to focus on extraction of low level features from video data and images. In the next parts of this work, there is described data set and results of experiments in applications RapidMiner, LibSVM and own developed application. The last chapter summarises results of used methods for high level feature extraction from low level description of data.
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Exploration of Multimedia Collections
Moško, Juraj ; Skopal, Tomáš (advisor)
Multimedia retrieval systems are supposed to provide the method and the interface for users to retrieve particular multimedia data from multimedia collections. Although, many different retrieval techniques evolved from times when the search in multimedia collections firstly appeared as a research task, not all of them can fulfill specific requirements that the multimedia exploration is determined for. The multimedia exploration is designated for revealing the content of a whole multimedia collection, quite often totally unknown to the users who retrieve data. Because of these facts a multimedia exploration system has to solve problems like, how to visualize (usually multidimensional) multimedia data, how to scale data retrieval from arbitrarily large collections and how to design such an interface that the users could intuitively use for the exploration. Taking these problems into consideration, we proposed and evaluated ideas for building the system that is well-suited for the multimedia exploration. We outlined the overall architecture of a multimedia exploration system, created the Multi-Layer Exploration Structure (MLES) as an underlying index structure that should solve problems of efficient and intuitive data retrieval and we also proposed definitions of exploration operations as an interactive and...
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Known-item search in image datasets using simple color sketches
Dräxler, Peter ; Lokoč, Jakub (advisor) ; Iser, Tomáš (referee)
With the growing amount of multimedia content, the availability of quality search tools is becoming increasingly important. Without suitable sample queries, it is difficult to evaluate quality of any search algorithm. In this work we search for a known image in a database. We describe an experiment in which 2,500 simple color drawings were collected from real users. Using these drawings, we evaluate the accuracy with which the user is able to remember the colors in the image. We use the obtained data to evaluate the accuracy of various search models. Part of the work is also a web application that allows you to search in images. 1
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Exploration of Multimedia Collections
Moško, Juraj ; Skopal, Tomáš (advisor) ; Schöffmann, Klaus (referee) ; Dohnal, Vlastislav (referee)
Multimedia retrieval systems are supposed to provide the method and the interface for users to retrieve particular multimedia data from multimedia collections. Although, many different retrieval techniques evolved from times when the search in multimedia collections firstly appeared as a research task, not all of them can fulfill specific requirements that the multimedia exploration is determined for. The multimedia exploration is designated for revealing the content of a whole multimedia collection, quite often totally unknown to the users who retrieve data. Because of these facts a multimedia exploration system has to solve problems like, how to visualize (usually multidimensional) multimedia data, how to scale data retrieval from arbitrarily large collections and how to design such an interface that the users could intuitively use for the exploration. Taking these problems into consideration, we proposed and evaluated ideas for building the system that is well-suited for the multimedia exploration. We outlined the overall architecture of a multimedia exploration system, created the Multi-Layer Exploration Structure (MLES) as an underlying index structure that should solve problems of efficient and intuitive data retrieval and we also proposed definitions of exploration operations as an interactive and...
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Exploration of Multimedia Collections
Moško, Juraj ; Skopal, Tomáš (advisor)
Multimedia retrieval systems are supposed to provide the method and the interface for users to retrieve particular multimedia data from multimedia collections. Although, many different retrieval techniques evolved from times when the search in multimedia collections firstly appeared as a research task, not all of them can fulfill specific requirements that the multimedia exploration is determined for. The multimedia exploration is designated for revealing the content of a whole multimedia collection, quite often totally unknown to the users who retrieve data. Because of these facts a multimedia exploration system has to solve problems like, how to visualize (usually multidimensional) multimedia data, how to scale data retrieval from arbitrarily large collections and how to design such an interface that the users could intuitively use for the exploration. Taking these problems into consideration, we proposed and evaluated ideas for building the system that is well-suited for the multimedia exploration. We outlined the overall architecture of a multimedia exploration system, created the Multi-Layer Exploration Structure (MLES) as an underlying index structure that should solve problems of efficient and intuitive data retrieval and we also proposed definitions of exploration operations as an interactive and...
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Knowledge Discovery in Image Databases
Jaroš, Ondřej ; Řezníček, Ivo (referee) ; Chmelař, Petr (advisor)
This thesis is focused on knowledge discovery from databases, especially on methods of classification and prediction. These methods are described in detail. Furthermore, this work deals with multimedia databases and the way these databases store data. In particular, the method for processing low-level image and video data is described. The practical part of the thesis focuses on the implementation of this GMM method used for extracting low-level features of video data and images. In other parts, input data and tools, which the implemented method was compared with, are described. The last section focuses on experiments comparing extraction efficiency features of high-level attributes of low-level data and the methods implemented in selected classification tools LibSVM.
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Multimodal Database Search
Krejčíř, Tomáš ; Stryka, Lukáš (referee) ; Chmelař, Petr (advisor)
The field that deals with storing and effective searching of multimedia documents is called Information retrieval. This paper describes solution of effective searching in collections of shots. Multimedia documents are presented as vectors in high-dimensional space, because in such collection of documents it is easier to define semantics as well as the mechanisms of searching. The work aims at problems of similarity searching based on metric space, which uses distance functions, such as Euclidean, Chebyshev or Mahalanobis, for comparing global features and cosine or binary rating for comparing local features. Experiments on the TRECVid dataset compare implemented distance functions. Best distance function for global features appears to be Mahalanobis and for local features cosine rating.
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