Master data

Title: VCA: video complexity analyzer
Subtitle:
Abstract:

For online analysis of the video content complexity in live streaming applications, selecting low-complexity features is critical to ensure low-latency video streaming without disruptions. To this light, for each video (segment), two features, i.e., the average texture energy and the average gradient of the texture energy, are determined. A DCT-based energy function is introduced to determine the block-wise texture of each frame. The spatial and temporal features of the video (segment) are derived from this DCT-based energy function. The Video Complexity Analyzer (VCA) project aims to provide an efficient spatial and temporal complexity analysis of each video (segment) which can be used in various applications to find the optimal encoding decisions. VCA leverages some of the x86 Single Instruction Multiple Data (SIMD) optimizations for Intel CPUs and multi-threading optimizations to achieve increased performance. VCA is an open-source library published under the GNU GPLv3 license.

Keywords: Video Complexity, Texture, SIMD, Multi-threading, Video Streaming
Publication type: Article in Proceedings (Authorship)
Publication date: 14.06.2022 (Print)
Published by: MMSys '22 Proceedings of the 13th ACM Multimedia Systems Conference
MMSys '22 Proceedings of the 13th ACM Multimedia Systems Conference
to publication
 ( ACM Press; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 259 - 264

Versionen

Keine Version vorhanden
Publication date: 14.06.2022
ISBN: -
ISSN: -
Homepage: https://dl.acm.org/doi/10.1145/3524273.3532896
Publication date: 05.08.2022
ISBN (e-book): -
eISSN: -
DOI: http://dx.doi.org/10.1145/3524273.3532896
Homepage: https://dl.acm.org/doi/10.1145/3524273.3532896
Open access
  • Available online (open access)

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Austria
   martina.steinbacher@aau.at
http://itec.aau.at/
To organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: II)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Communication

Cooperations

Organisation Address
bitmovin GmbH
Schleppe-Platz 7
9020 Klagenfurt am Wörthersee
Austria - Carinthia
Schleppe-Platz 7
AT - 9020  Klagenfurt am Wörthersee

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