The Konstanz natural video database (KoNViD-1k)

Vlad Hosu, Franz Hahn, Mohsen Jenadeleh, Hanhe Lin, Hui Men, Tamás Szirányi, Shujun Li, Dietmar Saupe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

198 Citations (Scopus)

Abstract

Subjective video quality assessment (VQA) strongly depends on semantics, context, and the types of visual distortions. Currently, all existing VQA databases include only a small number of video sequences with artificial distortions. The development and evaluation of objective quality assessment methods would benefit from having larger datasets of real-world video sequences with corresponding subjective mean opinion scores (MOS), in particular for deep learning purposes. In addition, the training and validation of any VQA method intended to be 'general purpose' requires a large dataset of video sequences that are representative of the whole spectrum of available video content and all types of distortions. We report our work on KoNViD-1k, a subjectively annotated VQA database consisting of 1,200 public-domain video sequences, fairly sampled from a large public video dataset, YFCC100m. We present the challenges and choices we have made in creating such a database aimed at 'in the wild' authentic distortions, depicting a wide variety of content.

Original languageEnglish
Title of host publication2017 9th International Conference on Quality of Multimedia Experience (QoMEX 2017)
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-5386-4024-1
ISBN (Print)978-1-5386-4025-8
DOIs
Publication statusPublished - 30 Jun 2017
Event9th International Conference on Quality of Multimedia Experience, QoMEX 2017 - Erfurt, Germany
Duration: 29 May 20172 Jun 2017

Publication series

Name2017 9th International Conference on Quality of Multimedia Experience, QoMEX 2017
PublisherIEEE
ISSN (Electronic)2472-7814

Conference

Conference9th International Conference on Quality of Multimedia Experience, QoMEX 2017
Country/TerritoryGermany
CityErfurt
Period29/05/172/06/17

Keywords

  • authentic video
  • crowdsourcing
  • fair sampling
  • Video database
  • video quality assessment

ASJC Scopus subject areas

  • Media Technology
  • Human-Computer Interaction
  • Safety, Risk, Reliability and Quality

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