Big Data Analysis for Media Production
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F15%3APU117072" target="_blank" >RIV/00216305:26230/15:PU117072 - isvavai.cz</a>
Výsledek na webu
<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7350093" target="_blank" >http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7350093</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/JPROC.2015.2496111" target="_blank" >10.1109/JPROC.2015.2496111</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Big Data Analysis for Media Production
Popis výsledku v původním jazyce
A typical high-end film production generates several terabytes of data per day, either as footage from multiple cameras or as background information regarding the set (laser scans, spherical captures, etc). This paper presents solutions to improve the integration of the multiple data sources, and understand their quality and content, which are useful both to support creative decisions on-set (or near it) and enhance the postproduction process. The main cinema specific contributions, tested on a multisource production dataset made publicly available for research purposes, are the monitoring and quality assurance of multicamera set-ups, multisource registration and acceleration of 3-D reconstruction, anthropocentric visual analysis techniques for semantic content annotation, and integrated 2-D-3-D web visualization tools. We discuss as well improvements carried out in basic techniques for acceleration, clustering and visualization, which were necessary to deal with the very large multisource data, and can be applied to other big data problems in diverse application fields.
Název v anglickém jazyce
Big Data Analysis for Media Production
Popis výsledku anglicky
A typical high-end film production generates several terabytes of data per day, either as footage from multiple cameras or as background information regarding the set (laser scans, spherical captures, etc). This paper presents solutions to improve the integration of the multiple data sources, and understand their quality and content, which are useful both to support creative decisions on-set (or near it) and enhance the postproduction process. The main cinema specific contributions, tested on a multisource production dataset made publicly available for research purposes, are the monitoring and quality assurance of multicamera set-ups, multisource registration and acceleration of 3-D reconstruction, anthropocentric visual analysis techniques for semantic content annotation, and integrated 2-D-3-D web visualization tools. We discuss as well improvements carried out in basic techniques for acceleration, clustering and visualization, which were necessary to deal with the very large multisource data, and can be applied to other big data problems in diverse application fields.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/7E13044" target="_blank" >7E13044: IMPART - Intelligent Management Platform for Advanced Real-Time media processes</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2015
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
IEEE Communication Letters
ISSN
1089-7798
e-ISSN
1558-2558
Svazek periodika
2015
Číslo periodika v rámci svazku
2
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
29
Strana od-do
1-29
Kód UT WoS článku
000386244000004
EID výsledku v databázi Scopus
2-s2.0-84949844845