This thesis investigates efficient manual image tagging approaches. It specifically focuses on organising images into clusters depending on their content, and thus on simplifying the selection of similar photos. Such selections may be efficiently tagged with common tags. The thesis investigates known techniques for visualisation of image collections according to the image content, together with dimensionality reduction methods. The most suitable methods are considered and evaluated. The thesis proposes a novel method for presenting image collections on 2D displays which combines a timeline with similarity grouping (Timeline projection). This method utilizes t-Distributed Stochastic Neighbour Embedding (t-SNE) for otpimally projecting groupings in high dimensional feature spaces onto the low-dimensional screen. Various modifications of t-SNE and ways to combine it with the timeline are discussed and chosen combination is implemented as a web interface and is qualitatively evaluated in a user study. Possible directions of further research on the subject are suggested.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:413348 |
Date | January 2013 |
Creators | Procházka, Václav |
Contributors | Zemčík, Pavel, Hradiš, Michal |
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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