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

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
Externally published	Yes
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/Territory	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

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 et al.

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

Sato, Yasuomi D. ; Jitsev, Jenia ; Bornschein, Joerg et al. / 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).

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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.

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A Gabor wavelet pyramid-based object detection algorithm

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Keywords

ASJC Scopus subject areas

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