Use of human motion biometrics for multiple-view registration

László Havasi, Zoltán Szlávik, T. Szirányi

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

2 Citations (Scopus)

Abstract

A novel image-registration method is presented which is applicable to multi-camera systems viewing human subjects in motion. The method is suitable for use with indoor or outdoor surveillance scenes. The paper summarizes an efficient walk-detection and biometric method for extraction of image characteristics which enables the walk properties of the viewed subjects to be used to establish corresponding image-points for the purpose of image-registration between cameras. The leading leg of the walking subject is a good feature to match, and the presented method can identify this from two successive walk-steps (one walk cycle). Using this approach, the described method can detect a sufficient number of corresponding points for the estimation of correspondence between views from two cameras. An evaluation study has demonstrated the method's feasibility in the context of an actual indoor real-time surveillance system.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages35-43
Number of pages9
Volume3708 LNCS
DOIs
Publication statusPublished - 2005
Event7th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2005 - Antwerp, Belgium
Duration: Sep 20 2005Sep 23 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3708 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2005
CountryBelgium
CityAntwerp
Period9/20/059/23/05

Fingerprint

Biometrics
Registration
Cameras
Image registration
Walk
Motion
Camera
Image Registration
Surveillance
Computer Systems
Walking
Human
Leg
Correspondence
Sufficient
Real-time
Cycle
Evaluation

ASJC Scopus subject areas

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

Cite this

Havasi, L., Szlávik, Z., & Szirányi, T. (2005). Use of human motion biometrics for multiple-view registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3708 LNCS, pp. 35-43). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3708 LNCS). https://doi.org/10.1007/11558484_5

Use of human motion biometrics for multiple-view registration. / Havasi, László; Szlávik, Zoltán; Szirányi, T.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3708 LNCS 2005. p. 35-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3708 LNCS).

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

Havasi, L, Szlávik, Z & Szirányi, T 2005, Use of human motion biometrics for multiple-view registration. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3708 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3708 LNCS, pp. 35-43, 7th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2005, Antwerp, Belgium, 9/20/05. https://doi.org/10.1007/11558484_5
Havasi L, Szlávik Z, Szirányi T. Use of human motion biometrics for multiple-view registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3708 LNCS. 2005. p. 35-43. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11558484_5
Havasi, László ; Szlávik, Zoltán ; Szirányi, T. / Use of human motion biometrics for multiple-view registration. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3708 LNCS 2005. pp. 35-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{49b103b84a5b48f79b6823397fd048d8,
title = "Use of human motion biometrics for multiple-view registration",
abstract = "A novel image-registration method is presented which is applicable to multi-camera systems viewing human subjects in motion. The method is suitable for use with indoor or outdoor surveillance scenes. The paper summarizes an efficient walk-detection and biometric method for extraction of image characteristics which enables the walk properties of the viewed subjects to be used to establish corresponding image-points for the purpose of image-registration between cameras. The leading leg of the walking subject is a good feature to match, and the presented method can identify this from two successive walk-steps (one walk cycle). Using this approach, the described method can detect a sufficient number of corresponding points for the estimation of correspondence between views from two cameras. An evaluation study has demonstrated the method's feasibility in the context of an actual indoor real-time surveillance system.",
author = "L{\'a}szl{\'o} Havasi and Zolt{\'a}n Szl{\'a}vik and T. Szir{\'a}nyi",
year = "2005",
doi = "10.1007/11558484_5",
language = "English",
isbn = "354029032X",
volume = "3708 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "35--43",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Use of human motion biometrics for multiple-view registration

AU - Havasi, László

AU - Szlávik, Zoltán

AU - Szirányi, T.

PY - 2005

Y1 - 2005

N2 - A novel image-registration method is presented which is applicable to multi-camera systems viewing human subjects in motion. The method is suitable for use with indoor or outdoor surveillance scenes. The paper summarizes an efficient walk-detection and biometric method for extraction of image characteristics which enables the walk properties of the viewed subjects to be used to establish corresponding image-points for the purpose of image-registration between cameras. The leading leg of the walking subject is a good feature to match, and the presented method can identify this from two successive walk-steps (one walk cycle). Using this approach, the described method can detect a sufficient number of corresponding points for the estimation of correspondence between views from two cameras. An evaluation study has demonstrated the method's feasibility in the context of an actual indoor real-time surveillance system.

AB - A novel image-registration method is presented which is applicable to multi-camera systems viewing human subjects in motion. The method is suitable for use with indoor or outdoor surveillance scenes. The paper summarizes an efficient walk-detection and biometric method for extraction of image characteristics which enables the walk properties of the viewed subjects to be used to establish corresponding image-points for the purpose of image-registration between cameras. The leading leg of the walking subject is a good feature to match, and the presented method can identify this from two successive walk-steps (one walk cycle). Using this approach, the described method can detect a sufficient number of corresponding points for the estimation of correspondence between views from two cameras. An evaluation study has demonstrated the method's feasibility in the context of an actual indoor real-time surveillance system.

UR - http://www.scopus.com/inward/record.url?scp=33646203836&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646203836&partnerID=8YFLogxK

U2 - 10.1007/11558484_5

DO - 10.1007/11558484_5

M3 - Conference contribution

SN - 354029032X

SN - 9783540290322

VL - 3708 LNCS

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

SP - 35

EP - 43

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

ER -