Robust 3D segmentation of multiple moving objects under weak perspective

Levente Hajder, D. Chetverikov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A scene containing multiple independently moving, possibly occluding, rigid objects is considered under the weak perspective camera model. We obtain a set of feature points tracked across a number of frames and address the problem of 3D motion segmentation of the objects in presence of measurement noise and outliers. We extend the robust structure from motion (SfM) method [5] to 3D motion segmentation and apply it to realistic, contaminated tracking data with occlusion. A number of approaches to 3D motion segmentation have already been proposed [3,6,14,15]. However, most of them were not developed for, and tested on, noisy and outlier-corrupted data that often occurs in practice. Due to the consistent use of robust techniques at all critical steps, our approach can cope with such data, as demonstrated in a number of tests with synthetic and real image sequences.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages48-59
Number of pages12
Volume4358 LNCS
DOIs
Publication statusPublished - 2007
Event2nd International Workshop on Dynamical Vision, WDV 2006 - 9th European Conference on Computer Vision,(ECCV 2006) - Graz, Austria
Duration: May 13 2006May 13 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4358 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Workshop on Dynamical Vision, WDV 2006 - 9th European Conference on Computer Vision,(ECCV 2006)
CountryAustria
CityGraz
Period5/13/065/13/06

Fingerprint

Motion Segmentation
Moving Objects
Segmentation
Cameras
Outlier
Structure from Motion
Feature Point
Image Sequence
Occlusion
Camera
Noise
Object
Model

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Hajder, L., & Chetverikov, D. (2007). Robust 3D segmentation of multiple moving objects under weak perspective. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4358 LNCS, pp. 48-59). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4358 LNCS). https://doi.org/10.1007/978-3-540-70932-9_4

Robust 3D segmentation of multiple moving objects under weak perspective. / Hajder, Levente; Chetverikov, D.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4358 LNCS 2007. p. 48-59 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4358 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hajder, L & Chetverikov, D 2007, Robust 3D segmentation of multiple moving objects under weak perspective. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4358 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4358 LNCS, pp. 48-59, 2nd International Workshop on Dynamical Vision, WDV 2006 - 9th European Conference on Computer Vision,(ECCV 2006), Graz, Austria, 5/13/06. https://doi.org/10.1007/978-3-540-70932-9_4
Hajder L, Chetverikov D. Robust 3D segmentation of multiple moving objects under weak perspective. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4358 LNCS. 2007. p. 48-59. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-70932-9_4
Hajder, Levente ; Chetverikov, D. / Robust 3D segmentation of multiple moving objects under weak perspective. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4358 LNCS 2007. pp. 48-59 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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