MDPV - Metric Distance Permutation Vocabulary

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Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
Název česky MDPV - Vizuální slovník založený na permutacích vzdáleností
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DOHNAL Vlastislav HOMOLA Tomáš ZEZULA Pavel

Rok publikování 2015
Druh Článek v odborném periodiku
Časopis / Zdroj Information Retrieval
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www http://link.springer.com/article/10.1007/s10791-014-9247-6
Doi http://dx.doi.org/10.1007/s10791-014-9247-6
Obor Informatika
Klíčová slova feature quantization; visual vocabulary; bag-of-features model; k-means clustering; metric distance permutation vocabulary
Popis Sub-image content-based similarity search forms an important operation in current image archives since it provides users with images that contain a query image as their part. Such a search can conveniently be implemented using the bag-of-features model. Its integral part is a construction of visual vocabulary. Most existing algorithms to create a visual vocabulary suffer from high computational (e.g. k-means) or supervisor-guidance (e.g. visual-bit classifier, or sparse coding) requirements. In this paper, we propose a~novel approach to visual vocabulary construction called Metric Distance Permutation Vocabulary (MDPV). It is based on permutations of metric distances to create compact visual words. Its major advantage over prior techniques is time and space efficiency of vocabulary construction and quantization process during querying, while achieving comparable or even better effectiveness (query result quality). Moreover, this basic concept is extended to combine more independent permutations. Both the proposals are experimented on well-known real-world data-sets and compared to other state-of-the-art techniques.
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