3D object matching based on spherical Hilbert scanning

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

1 Citation (Scopus)

Abstract

This paper describes a novel method to match objects in cluttered scenes. This method makes use of Hilbert scanning of feature points in Hough space. We use a 3D Hough transform to obtain a spectrum on which 3D features are concentrated on the sphere. Then, based on the obtained Hough Spectrum, we apply Hilbert scanning on the sphere to match the objects. Using this approach, we can match the object correctly and robustly in both overlapping and noise situation. The characteristic of this method is that it is a global matching method without an estimate of the rotation first and suffering from computational complexity brought by voting/correlation procedure. The experiment results show that the method is more effective compared to existing methods in both matching rate and robustness.

Original languageEnglish
Title of host publicationProceedings - International Conference on Image Processing, ICIP
Pages2941-2944
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong
Duration: 2010 Sep 262010 Sep 29

Other

Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
CityHong Kong
Period10/9/2610/9/29

Fingerprint

Scanning
Hough transforms
Computational complexity
Experiments

Keywords

  • Hilbert scanning
  • Hough transform
  • Pattern matching
  • Three-dimension point matching

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Tong, C., & Kamata, S. (2010). 3D object matching based on spherical Hilbert scanning. In Proceedings - International Conference on Image Processing, ICIP (pp. 2941-2944). [5652180] https://doi.org/10.1109/ICIP.2010.5652180

3D object matching based on spherical Hilbert scanning. / Tong, Can; Kamata, Seiichiro.

Proceedings - International Conference on Image Processing, ICIP. 2010. p. 2941-2944 5652180.

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

Tong, C & Kamata, S 2010, 3D object matching based on spherical Hilbert scanning. in Proceedings - International Conference on Image Processing, ICIP., 5652180, pp. 2941-2944, 2010 17th IEEE International Conference on Image Processing, ICIP 2010, Hong Kong, 10/9/26. https://doi.org/10.1109/ICIP.2010.5652180
Tong C, Kamata S. 3D object matching based on spherical Hilbert scanning. In Proceedings - International Conference on Image Processing, ICIP. 2010. p. 2941-2944. 5652180 https://doi.org/10.1109/ICIP.2010.5652180
Tong, Can ; Kamata, Seiichiro. / 3D object matching based on spherical Hilbert scanning. Proceedings - International Conference on Image Processing, ICIP. 2010. pp. 2941-2944
@inproceedings{43296955ad4b4da99b9bafe8e02474f8,
title = "3D object matching based on spherical Hilbert scanning",
abstract = "This paper describes a novel method to match objects in cluttered scenes. This method makes use of Hilbert scanning of feature points in Hough space. We use a 3D Hough transform to obtain a spectrum on which 3D features are concentrated on the sphere. Then, based on the obtained Hough Spectrum, we apply Hilbert scanning on the sphere to match the objects. Using this approach, we can match the object correctly and robustly in both overlapping and noise situation. The characteristic of this method is that it is a global matching method without an estimate of the rotation first and suffering from computational complexity brought by voting/correlation procedure. The experiment results show that the method is more effective compared to existing methods in both matching rate and robustness.",
keywords = "Hilbert scanning, Hough transform, Pattern matching, Three-dimension point matching",
author = "Can Tong and Seiichiro Kamata",
year = "2010",
doi = "10.1109/ICIP.2010.5652180",
language = "English",
isbn = "9781424479948",
pages = "2941--2944",
booktitle = "Proceedings - International Conference on Image Processing, ICIP",

}

TY - GEN

T1 - 3D object matching based on spherical Hilbert scanning

AU - Tong, Can

AU - Kamata, Seiichiro

PY - 2010

Y1 - 2010

N2 - This paper describes a novel method to match objects in cluttered scenes. This method makes use of Hilbert scanning of feature points in Hough space. We use a 3D Hough transform to obtain a spectrum on which 3D features are concentrated on the sphere. Then, based on the obtained Hough Spectrum, we apply Hilbert scanning on the sphere to match the objects. Using this approach, we can match the object correctly and robustly in both overlapping and noise situation. The characteristic of this method is that it is a global matching method without an estimate of the rotation first and suffering from computational complexity brought by voting/correlation procedure. The experiment results show that the method is more effective compared to existing methods in both matching rate and robustness.

AB - This paper describes a novel method to match objects in cluttered scenes. This method makes use of Hilbert scanning of feature points in Hough space. We use a 3D Hough transform to obtain a spectrum on which 3D features are concentrated on the sphere. Then, based on the obtained Hough Spectrum, we apply Hilbert scanning on the sphere to match the objects. Using this approach, we can match the object correctly and robustly in both overlapping and noise situation. The characteristic of this method is that it is a global matching method without an estimate of the rotation first and suffering from computational complexity brought by voting/correlation procedure. The experiment results show that the method is more effective compared to existing methods in both matching rate and robustness.

KW - Hilbert scanning

KW - Hough transform

KW - Pattern matching

KW - Three-dimension point matching

UR - http://www.scopus.com/inward/record.url?scp=78651095806&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78651095806&partnerID=8YFLogxK

U2 - 10.1109/ICIP.2010.5652180

DO - 10.1109/ICIP.2010.5652180

M3 - Conference contribution

SN - 9781424479948

SP - 2941

EP - 2944

BT - Proceedings - International Conference on Image Processing, ICIP

ER -