MDPV - Metric Distance Permutation Vocabulary

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F15%3A00080599" target="_blank" >RIV/00216224:14330/15:00080599 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s10791-014-9247-6" target="_blank" >http://dx.doi.org/10.1007/s10791-014-9247-6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10791-014-9247-6" target="_blank" >10.1007/s10791-014-9247-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

MDPV - Metric Distance Permutation Vocabulary

Popis výsledku v původním jazyce

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 andspace 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 per

Název v anglickém jazyce

MDPV - Metric Distance Permutation Vocabulary

Popis výsledku anglicky

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 andspace 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 per

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Centrum pro multi-modální interpretaci dat velkého rozsahu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Information Retrieval

ISSN

1386-4564

e-ISSN

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Svazek periodika

18

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

22

Strana od-do

51-72

Kód UT WoS článku

000348350600003

EID výsledku v databázi Scopus

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