Fundamental matrices from moving objects using line motion barcodes

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

doi:10.1007/978-3-319-46475-6_14

Fundamental matrices from moving objects using line motion barcodes

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

^*Corresponding author for this work

The Rachel and Selim Benin School of Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Computer Vision - 14th European Conference, ECCV 2016, Proceedings
Editors	Bastian Leibe, Nicu Sebe, Max Welling, Jiri Matas
Publisher	Springer Verlag
Pages	220-228
Number of pages	9
ISBN (Print)	9783319464749
DOIs	https://doi.org/10.1007/978-3-319-46475-6_14
State	Published - 2016
Event	14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands Duration: 8 Oct 2016 → 16 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9906 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th European Conference on Computer Vision, ECCV 2016
Country/Territory	Netherlands
City	Amsterdam
Period	8/10/16 → 16/10/16

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2016.

Keywords

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

Access to Document

10.1007/978-3-319-46475-6_14

Cite this

Kasten, Y., Ben-Artzi, G., Peleg, S., & Werman, M. (2016). Fundamental matrices from moving objects using line motion barcodes. In B. Leibe, N. Sebe, M. Welling, & J. Matas (Eds.), Computer Vision - 14th European Conference, ECCV 2016, Proceedings (pp. 220-228). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9906 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46475-6_14

Kasten, Yoni ; Ben-Artzi, Gil ; Peleg, Shmuel et al. / Fundamental matrices from moving objects using line motion barcodes. Computer Vision - 14th European Conference, ECCV 2016, Proceedings. editor / Bastian Leibe ; Nicu Sebe ; Max Welling ; Jiri Matas. Springer Verlag, 2016. pp. 220-228 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{7afb613b24d646618cb014ff10279c74,

title = "Fundamental matrices from moving objects using line motion barcodes",

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.",

keywords = "Epipolar geometry, Epipolar lines, Fundamental matrix, Motion barcodes, Multi-camera calibration",

author = "Yoni Kasten and Gil Ben-Artzi and Shmuel Peleg and Michael Werman",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 14th European Conference on Computer Vision, ECCV 2016 ; Conference date: 08-10-2016 Through 16-10-2016",

year = "2016",

doi = "10.1007/978-3-319-46475-6_14",

language = "אנגלית",

isbn = "9783319464749",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "220--228",

editor = "Bastian Leibe and Nicu Sebe and Max Welling and Jiri Matas",

booktitle = "Computer Vision - 14th European Conference, ECCV 2016, Proceedings",

address = "גרמניה",

}

Kasten, Y, Ben-Artzi, G, Peleg, S & Werman, M 2016, Fundamental matrices from moving objects using line motion barcodes. in B Leibe, N Sebe, M Welling & J Matas (eds), Computer Vision - 14th European Conference, ECCV 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9906 LNCS, Springer Verlag, pp. 220-228, 14th European Conference on Computer Vision, ECCV 2016, Amsterdam, Netherlands, 8/10/16. https://doi.org/10.1007/978-3-319-46475-6_14

Fundamental matrices from moving objects using line motion barcodes. / Kasten, Yoni; Ben-Artzi, Gil; Peleg, Shmuel et al.
Computer Vision - 14th European Conference, ECCV 2016, Proceedings. ed. / Bastian Leibe; Nicu Sebe; Max Welling; Jiri Matas. Springer Verlag, 2016. p. 220-228 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9906 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fundamental matrices from moving objects using line motion barcodes

AU - Kasten, Yoni

AU - Ben-Artzi, Gil

AU - Peleg, Shmuel

AU - Werman, Michael

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Epipolar geometry

KW - Epipolar lines

KW - Fundamental matrix

KW - Motion barcodes

KW - Multi-camera calibration

UR - http://www.scopus.com/inward/record.url?scp=84990831225&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-46475-6_14

DO - 10.1007/978-3-319-46475-6_14

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:84990831225

SN - 9783319464749

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 220

EP - 228

BT - Computer Vision - 14th European Conference, ECCV 2016, Proceedings

A2 - Leibe, Bastian

A2 - Sebe, Nicu

A2 - Welling, Max

A2 - Matas, Jiri

PB - Springer Verlag

T2 - 14th European Conference on Computer Vision, ECCV 2016

Y2 - 8 October 2016 through 16 October 2016

ER -

Kasten Y, Ben-Artzi G, Peleg S, Werman M. Fundamental matrices from moving objects using line motion barcodes. In Leibe B, Sebe N, Welling M, Matas J, editors, Computer Vision - 14th European Conference, ECCV 2016, Proceedings. Springer Verlag. 2016. p. 220-228. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46475-6_14

Fundamental matrices from moving objects using line motion barcodes

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this