Video stitching for linear camera arrays

Wei Sheng Lai, Orazio Gallo, Jinwei Gu, Deqing Sun, Ming Hsuan Yang, Jan Kautz

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

Despite the long history of image and video stitching research, existing academic and commercial solutions still produce strong artifacts. In this work, we propose a wide-baseline video stitching algorithm for linear camera arrays that is temporally stable and tolerant to strong parallax. Our key insight is that stitching can be cast as a problem of learning a smooth spatial interpolation between the input videos. To solve this problem, inspired by pushbroom cameras, we introduce a fast pushbroom interpolation layer and propose a novel pushbroom stitching network, which learns a dense flow field to smoothly align the multiple input videos for spatial interpolation. Our approach outperforms the state-of-the-art by a significant margin, as we show with a user study, and has immediate applications in many areas such as virtual reality, immersive telepresence, autonomous driving, and video surveillance.

Original languageEnglish
Publication statusPublished - 2020
Event30th British Machine Vision Conference, BMVC 2019 - Cardiff, United Kingdom
Duration: 2019 Sep 92019 Sep 12

Conference

Conference30th British Machine Vision Conference, BMVC 2019
Country/TerritoryUnited Kingdom
CityCardiff
Period19/9/919/9/12

Bibliographical note

Publisher Copyright:
© 2019. The copyright of this document resides with its authors.

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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