Fundamental matrices from moving objects using line motion barcodes

Yoni Kasten, Gil Ben-Artzi, Shmuel Peleg, Michael Werman

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

7 Scopus citations

Abstract

Computing the epipolar geometry between cameras with very different viewpoints is often very difficult. The appearance of objects can vary greatly, and it is difficult to find corresponding feature points. Prior methods searched for corresponding epipolar lines using points on the convex hull of the silhouette of a single moving object. These methods fail when the scene includes multiple moving objects. This paper extends previous work to scenes having multiple moving objects by using the "Motion Barcodes", a temporal signature of lines. Corresponding epipolar lines have similar motion barcodes, and candidate pairs of corresponding epipoar lines are found by the similarity of their motion barcodes. As in previous methods we assume that cameras are relatively stationary and that moving objects have already been extracted using background subtraction.

Original languageEnglish
Title of host publicationComputer Vision - 14th European Conference, ECCV 2016, Proceedings
EditorsBastian Leibe, Nicu Sebe, Max Welling, Jiri Matas
Pages220-228
Number of pages9
DOIs
StatePublished - 2016
Externally publishedYes
Event14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
Duration: 8 Oct 201616 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9906 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th European Conference on Computer Vision, ECCV 2016
Country/TerritoryNetherlands
CityAmsterdam
Period8/10/1616/10/16

Keywords

  • Epipolar geometry
  • Epipolar lines
  • Fundamental matrix
  • Motion barcodes
  • Multi-camera calibration

Fingerprint

Dive into the research topics of 'Fundamental matrices from moving objects using line motion barcodes'. Together they form a unique fingerprint.

Cite this