An Epipolar Line from a Single Pixel

Tavi Halperin, Michael Werman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Computing the epipolar geometry from feature points between cameras with very different viewpoints is often error prone, as an object's appearance can vary greatly between images. For such cases, it has been shown that using motion extracted from video can achieve much better results than using a static image. This paper extends these earlier works based on the scene dynamics. In this paper we propose a new method to compute the epipolar geometry from a video stream, by exploiting the following observation: For a pixel p in Image A, all pixels corresponding to p in Image B are on the same epipolar line. Equivalently, the image of the line going through camera A's center and p is an epipolar line in B. Therefore, when cameras A and B are synchronized, the momentary images of two objects projecting to the same pixel, p, in camera A at times t1 and t2, lie on an epipolar line in camera B. Based on this observation we achieve fast and precise computation of epipolar lines. Calibrating cameras based on our method of finding epipolar lines is much faster and more robust than previous methods.

Original languageAmerican English
Title of host publicationProceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages983-991
Number of pages9
ISBN (Electronic)9781538648865
DOIs
StatePublished - 3 May 2018
Event18th IEEE Winter Conference on Applications of Computer Vision, WACV 2018 - Lake Tahoe, United States
Duration: 12 Mar 201815 Mar 2018

Publication series

NameProceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018
Volume2018-January

Conference

Conference18th IEEE Winter Conference on Applications of Computer Vision, WACV 2018
Country/TerritoryUnited States
CityLake Tahoe
Period12/03/1815/03/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

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