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.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:236739 |
| Date | January 2009 |
| Creators | Krejčíř, Tomáš |
| Contributors | Stryka, Lukáš, Chmelař, Petr |
| Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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