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Big data analysis for media production

Big data analysis for media production
Big data analysis for media production
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. © 1963-2012 IEEE.
Big data, Data integration, Data visualization, Image reconstruction, Information analysis, Quality assurance, Quality control, Semantic Web, Semantics, Visualization, 3D reconstruction, 3D Visualization, Graph processing, Multi-modal data, Semantic video analysis, Three dimensional computer graphics
0018-9219
2085-2113
Blat, J.
25b3e3d8-930e-4d0a-82c3-1d98c0aa38dc
Evans, A.
5dde4f29-1c4d-42de-8f72-527fc0c4afab
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Imre, E.
d5e10a85-873f-4e03-80b4-d6c3f4c6ca3d
Polok, L.
76afc50a-4c97-4449-8d89-15b88df23a1c
Ila, V.
699c4e52-9c1d-4bf2-b64d-dae91e5046df
Nikolaidis, N.
02887138-3702-439d-ad06-a5a07befbc86
Zemčík, P.
a058a2ab-3c70-48ea-8772-53e0b91a62bf
Tefas, A.
79348442-4404-46bd-a2f2-aeb9530f36bd
Smrž, P.
1b463163-147c-4890-bd51-f1ffcafc07c8
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
Pitas, I.
dd013502-b2cf-45d9-bfdf-f1bcdedf453c
Blat, J.
25b3e3d8-930e-4d0a-82c3-1d98c0aa38dc
Evans, A.
5dde4f29-1c4d-42de-8f72-527fc0c4afab
Kim, H.
2c7c135c-f00b-4409-acb2-85b3a9e8225f
Imre, E.
d5e10a85-873f-4e03-80b4-d6c3f4c6ca3d
Polok, L.
76afc50a-4c97-4449-8d89-15b88df23a1c
Ila, V.
699c4e52-9c1d-4bf2-b64d-dae91e5046df
Nikolaidis, N.
02887138-3702-439d-ad06-a5a07befbc86
Zemčík, P.
a058a2ab-3c70-48ea-8772-53e0b91a62bf
Tefas, A.
79348442-4404-46bd-a2f2-aeb9530f36bd
Smrž, P.
1b463163-147c-4890-bd51-f1ffcafc07c8
Hilton, Adrian
12782a55-4c4d-4dfb-a690-62505f6665db
Pitas, I.
dd013502-b2cf-45d9-bfdf-f1bcdedf453c

Blat, J., Evans, A., Kim, H., Imre, E., Polok, L., Ila, V., Nikolaidis, N., Zemčík, P., Tefas, A., Smrž, P., Hilton, Adrian and Pitas, I. (2016) Big data analysis for media production. Proceedings of the IEEE, 104 (11), 2085-2113. (doi:10.1109/JPROC.2015.2496111).

Record type: Article

Abstract

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. © 1963-2012 IEEE.

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More information

e-pub ahead of print date: 9 December 2015
Published date: November 2016
Additional Information: cited By 6
Keywords: Big data, Data integration, Data visualization, Image reconstruction, Information analysis, Quality assurance, Quality control, Semantic Web, Semantics, Visualization, 3D reconstruction, 3D Visualization, Graph processing, Multi-modal data, Semantic video analysis, Three dimensional computer graphics

Identifiers

Local EPrints ID: 440596
URI: http://eprints.soton.ac.uk/id/eprint/440596
ISSN: 0018-9219
PURE UUID: c2852ce6-0ac6-4053-92a9-45cfc02e4ae2
ORCID for H. Kim: ORCID iD orcid.org/0000-0003-4907-0491

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Date deposited: 12 May 2020 16:30
Last modified: 23 May 2020 00:47

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Contributors

Author: J. Blat
Author: A. Evans
Author: H. Kim ORCID iD
Author: E. Imre
Author: L. Polok
Author: V. Ila
Author: N. Nikolaidis
Author: P. Zemčík
Author: A. Tefas
Author: P. Smrž
Author: Adrian Hilton
Author: I. Pitas

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