Blind video temporal consistency

  • Nicolas Bonneel
  • , James Tompkin
  • , Kalyan Sunkavalli
  • , Deqing Sun
  • , Sylvain Paris
  • , Hanspeter Pfister

Research output: Contribution to journalArticlepeer-review

Abstract

Extending image processing techniques to videos is a non-trivial task; applying processing independently to each video frame often leads to temporal inconsistencies, and explicitly encoding temporal consistency requires algorithmic changes. We describe a more general approach to temporal consistency. We propose a gradient-domain technique that is blind to the particular image processing algorithm. Our technique takes a series of processed frames that suffers from flickering and generates a temporally-consistent video sequence. The core of our solution is to infer the temporal regularity from the original unprocessed video, and use it as a temporal consistency guide to stabilize the processed sequence. We formally characterize the frequency properties of our technique, and demonstrate, in practice, its ability to stabilize a wide range of popular image processing techniques including enhancement and stylization of color and tone, intrinsic images, and depth estimation.

Original languageEnglish
Article number196
JournalACM Transactions on Graphics
Volume34
Issue number6
DOIs
Publication statusPublished - 1 Nov 2015
Externally publishedYes

Keywords

  • Temporal consistency
  • Video processing

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