3 years ago

Toward an objective benchmark for video completion

Alexander Bokov, Dmitriy Vatolin, Mikhail Erofeev, Yury Gitman


Video-completion methods aim to complete selected regions of a video sequence in a natural looking manner with little to no additional user interaction. Numerous algorithms were proposed to solve this problem; however, a unified benchmark to quantify the progress in the field is still lacking. Video-completion results are usually judged by their plausibility and aren’t expected to adhere to one ground-truth result, which complicates measuring the video-completion performance. In this paper, we address this problem by proposing a set of full-reference quality metrics that outperform naïve approaches and an online benchmark for video-completion algorithms. We construct seven test sequences with ground-truth video-completion results by composing various foreground objects over a set of background videos. Using this dataset, we conduct an extensive comparative study of video-completion perceptual quality involving six algorithms and over 300 human participants. Finally, we show that by relaxing the requirement of complete adherence to ground truth and by taking into account temporal consistency we can increase the correlation of objective quality metrics with perceptual completion quality on the proposed dataset.

Publisher URL: https://link.springer.com/article/10.1007/s11760-018-1387-5

DOI: 10.1007/s11760-018-1387-5

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.