Effectiveness of the Bag-of-Words approach on the object search problem in 3D domain

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F17%3APU127339" target="_blank" >RIV/00216305:26230/17:PU127339 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/11640/" target="_blank" >https://www.fit.vut.cz/research/publication/11640/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3154353.3154365" target="_blank" >10.1145/3154353.3154365</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Effectiveness of the Bag-of-Words approach on the object search problem in 3D domain

Popis výsledku v původním jazyce

In this work, we investigate the application of the Bag-of-Words approach for object search task in 3D domain. Image retrieval task solutions, operating on datasets of thousands and millions images, have proved the effectiveness of Bag-of-Words approach. The availability of low cost RGB-D cameras is a rise of large datasets of 3D data similar to image corpuses (e.g. RoboEarth). The results of such an investigation could be useful for many robot scenarios like place recognition from a large dataset of samples of places acquired during the long-term observation of an environment. The first goal of our research presented in this paper is focused on the sensitivity of the Bag-of-Words approach to various parameters (e.g. spacial sampling, surface description etc.) with respect to precision, stability and robustness. The experiments are carry out on two widely-used datasets in object instance identification task in 3D domain.

Název v anglickém jazyce

Effectiveness of the Bag-of-Words approach on the object search problem in 3D domain

Popis výsledku anglicky

In this work, we investigate the application of the Bag-of-Words approach for object search task in 3D domain. Image retrieval task solutions, operating on datasets of thousands and millions images, have proved the effectiveness of Bag-of-Words approach. The availability of low cost RGB-D cameras is a rise of large datasets of 3D data similar to image corpuses (e.g. RoboEarth). The results of such an investigation could be useful for many robot scenarios like place recognition from a large dataset of samples of places acquired during the long-term observation of an environment. The first goal of our research presented in this paper is focused on the sensitivity of the Bag-of-Words approach to various parameters (e.g. spacial sampling, surface description etc.) with respect to precision, stability and robustness. The experiments are carry out on two widely-used datasets in object instance identification task in 3D domain.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of SCCG 2017

ISBN

978-1-4503-5107-2

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

138-145

Název nakladatele

Association for Computing Machinery

Místo vydání

New York City, NY

Místo konání akce

Mikulov

Datum konání akce

19. 4. 2017

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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