A Gabor wavelet pyramid-based object detection algorithm

Yasuomi D. Sato; Jenia Jitsev; Joerg Bornschein; Daniela Pamplona; Christian Keck; Christoph Von Der Malsburg

doi:10.1007/978-3-642-21090-7_28

A Gabor wavelet pyramid-based object detection algorithm

Yasuomi D. Sato, Jenia Jitsev, Joerg Bornschein, Daniela Pamplona, Christian Keck, Christoph Von Der Malsburg

INF - System Information Sciences

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

2 Citations (Scopus)

Abstract

We introduce visual object detection architecture, making full use of technical merits of so-called multi-scale feature correspondence in the neurally inspired Gabor pyramid. The remarkable property of the multi-scale Gabor feature correspondence is found with scale-space approaches, which an original image Gabor-filtered with the individual frequency levels is approximated to the correspondingly sub-sampled image smoothed with the low-pass filter. The multi-scale feature correspondence is used for effectively reducing computational costs in filtering. In particular, we show that the multi-scale Gabor feature correspondence play an effective role in matching between an input image and the model representation for object detection.

Original language	English
Title of host publication	Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011
Pages	232-240
Number of pages	9
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-21090-7_28
Publication status	Published - 2011
Event	8th International Symposium on Neural Networks, ISNN 2011 - Guilin, China Duration: 2011 May 29 → 2011 Jun 1

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6676 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	8th International Symposium on Neural Networks, ISNN 2011
Country	China
City	Guilin
Period	11/5/29 → 11/6/1

Keywords

Computer Vision
Gabor Pyramid
Multi-scale Feature Correspondence
Visual Object Detection

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-21090-7_28

Fingerprint Dive into the research topics of 'A Gabor wavelet pyramid-based object detection algorithm'. Together they form a unique fingerprint.

Cite this

Sato, Y. D., Jitsev, J., Bornschein, J., Pamplona, D., Keck, C., & Von Der Malsburg, C. (2011). A Gabor wavelet pyramid-based object detection algorithm. In Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011 (PART 2 ed., pp. 232-240). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6676 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-21090-7_28

A Gabor wavelet pyramid-based object detection algorithm. / Sato, Yasuomi D.; Jitsev, Jenia; Bornschein, Joerg; Pamplona, Daniela; Keck, Christian; Von Der Malsburg, Christoph.

Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011. PART 2. ed. 2011. p. 232-240 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6676 LNCS, No. PART 2).

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

Sato, YD, Jitsev, J, Bornschein, J, Pamplona, D, Keck, C & Von Der Malsburg, C 2011, A Gabor wavelet pyramid-based object detection algorithm. in Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6676 LNCS, pp. 232-240, 8th International Symposium on Neural Networks, ISNN 2011, Guilin, China, 11/5/29. https://doi.org/10.1007/978-3-642-21090-7_28

Sato YD, Jitsev J, Bornschein J, Pamplona D, Keck C, Von Der Malsburg C. A Gabor wavelet pyramid-based object detection algorithm. In Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011. PART 2 ed. 2011. p. 232-240. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-642-21090-7_28

Sato, Yasuomi D. ; Jitsev, Jenia ; Bornschein, Joerg ; Pamplona, Daniela ; Keck, Christian ; Von Der Malsburg, Christoph. / A Gabor wavelet pyramid-based object detection algorithm. Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011. PART 2. ed. 2011. pp. 232-240 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{e1c8cc1e36f344bd931ab4ca2781ae8c,

title = "A Gabor wavelet pyramid-based object detection algorithm",

abstract = "We introduce visual object detection architecture, making full use of technical merits of so-called multi-scale feature correspondence in the neurally inspired Gabor pyramid. The remarkable property of the multi-scale Gabor feature correspondence is found with scale-space approaches, which an original image Gabor-filtered with the individual frequency levels is approximated to the correspondingly sub-sampled image smoothed with the low-pass filter. The multi-scale feature correspondence is used for effectively reducing computational costs in filtering. In particular, we show that the multi-scale Gabor feature correspondence play an effective role in matching between an input image and the model representation for object detection.",

keywords = "Computer Vision, Gabor Pyramid, Multi-scale Feature Correspondence, Visual Object Detection",

author = "Sato, {Yasuomi D.} and Jenia Jitsev and Joerg Bornschein and Daniela Pamplona and Christian Keck and {Von Der Malsburg}, Christoph",

year = "2011",

doi = "10.1007/978-3-642-21090-7_28",

language = "English",

isbn = "9783642210891",

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

number = "PART 2",

pages = "232--240",

booktitle = "Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011",

edition = "PART 2",

}

TY - GEN

T1 - A Gabor wavelet pyramid-based object detection algorithm

AU - Sato, Yasuomi D.

AU - Jitsev, Jenia

AU - Bornschein, Joerg

AU - Pamplona, Daniela

AU - Keck, Christian

AU - Von Der Malsburg, Christoph

PY - 2011

Y1 - 2011

N2 - We introduce visual object detection architecture, making full use of technical merits of so-called multi-scale feature correspondence in the neurally inspired Gabor pyramid. The remarkable property of the multi-scale Gabor feature correspondence is found with scale-space approaches, which an original image Gabor-filtered with the individual frequency levels is approximated to the correspondingly sub-sampled image smoothed with the low-pass filter. The multi-scale feature correspondence is used for effectively reducing computational costs in filtering. In particular, we show that the multi-scale Gabor feature correspondence play an effective role in matching between an input image and the model representation for object detection.

AB - We introduce visual object detection architecture, making full use of technical merits of so-called multi-scale feature correspondence in the neurally inspired Gabor pyramid. The remarkable property of the multi-scale Gabor feature correspondence is found with scale-space approaches, which an original image Gabor-filtered with the individual frequency levels is approximated to the correspondingly sub-sampled image smoothed with the low-pass filter. The multi-scale feature correspondence is used for effectively reducing computational costs in filtering. In particular, we show that the multi-scale Gabor feature correspondence play an effective role in matching between an input image and the model representation for object detection.

KW - Computer Vision

KW - Gabor Pyramid

KW - Multi-scale Feature Correspondence

KW - Visual Object Detection

UR - http://www.scopus.com/inward/record.url?scp=79957856156&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79957856156&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-21090-7_28

DO - 10.1007/978-3-642-21090-7_28

M3 - Conference contribution

AN - SCOPUS:79957856156

SN - 9783642210891

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

SP - 232

EP - 240

BT - Advances in Neural Networks - 8th International Symposium on Neural Networks, ISNN 2011

T2 - 8th International Symposium on Neural Networks, ISNN 2011

Y2 - 29 May 2011 through 1 June 2011

ER -

A Gabor wavelet pyramid-based object detection algorithm

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Cite this