Image Stitching with Locally Shared Rotation Axis


Daniel Barath, Yaqing Ding, Zuzana Kukelova and Viktor Larsson


We consider the problem of stitching image sequences with cameras undergoing pure rotational motion. We leverage the assumption of a locally constant rotation axis, i.e., neighboring frames have a shared but unknown rotation axis. This assumption holds in many common image capturing scenarios, e.g., panoramic sweeping motions. Using this additional constraint, we develop techniques for three-view camera rotation estimation; a minimal solver for the two-view estimation with a known rotation axis; and a globally optimal robust estimator for the two-view case. We show on publicly available datasets that the proposed methods lead to camera rotation estimation superior to the state-of-the-art in terms of accuracy with comparable run-time. The source code will be made available.

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  Important Dates

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Paper registration July 23 30, 2021
Paper submission July 30, 2021
Supplementary August 8, 2021
Tutorial submission August 15, 2021
Tutorial notification August 31, 2021
Rebuttal period September 16-22, 2021
Paper notification October 1, 2021
Camera ready October 15, 2021
Demo submission July 30 Nov 15, 2021
Demo notification Oct 1 Nov 19, 2021
Tutorial November 30, 2021
Main conference December 1-3, 2021