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International Conference on Neural Information Processing

ICONIP 2010: Neural Information Processing. Models and Applications pp 352–359Cite as

Range Image Registration Using Particle Filter and Competitive Associative Nets

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6444))

Abstract

This paper presents a method using a particle filter (PF) and competitive associative nets (CAN2s) for range image registration to fuse 3D surfaces on range images taken from around an object by the laser range finder (LRF). The method uses the CAN2 for learning to provide a piecewise linear approximation of the LRF data involving various noise, and obtaining a coarse but fast pair-wise registration. The PF is used for reducing the cumulative error of the consecutive pair-wise registration. The effectiveness is shown by using the real LRF data of a rectangular box.

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References

  1. Salvi, J., Matabosh, C., Foli, D., Forest, J.: A review of recent range image registration methods. Image and Vision Computing 25, 578–596 (2007)

    Article  Google Scholar 

  2. Doucet, A., Feitas, N., Gordon, N. (eds.): Sequential Monte Carlo methods in particle. Springer, Heidelberg (2001)

    MATH  Google Scholar 

  3. Thrun, S., Burgard, W., Fox, D.: Probabilistic robotics. MIT Press, Cambridge (2005)

    MATH  Google Scholar 

  4. Kurogi, S., Koya, H., Nagashima, R., Wakeyama, D., Nishida, T.: Range image registration using plane extraction by the CAN2. In: Proc. CIRA 2009 (2009)

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  5. Kurogi, S.: Plane extraction from range data using competitive associative nets. The Brain & Neural Networks (Journal of Japanese Neural Network Society) 14(4), 273–281 (2007)

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Author information

Authors and Affiliations

  1. Kyusyu Institute of technology, Tobata, Kitakyushu, Fukuoka, 804-8550, Japan

    Shuichi Kurogi, Tomokazu Nagi & Takeshi Nishida

Authors
  1. Shuichi Kurogi
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  2. Tomokazu Nagi
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  3. Takeshi Nishida
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Editor information

Editors and Affiliations

  1. School of Information Technology, Murdoch University, 6150, Murdoch, WA, Australia

    Kok Wai Wong

  2. The Australian National University, 0200, Canberra, ACT, Australia

    B. Sumudu U. Mendis

  3. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Northfields Avenue, 2522, P.O. Box, Wollongong, NSW, Australia

    Abdesselam Bouzerdoum

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© 2010 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kurogi, S., Nagi, T., Nishida, T. (2010). Range Image Registration Using Particle Filter and Competitive Associative Nets. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Models and Applications. ICONIP 2010. Lecture Notes in Computer Science, vol 6444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17534-3_43

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  • DOI: https://doi.org/10.1007/978-3-642-17534-3_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17533-6

  • Online ISBN: 978-3-642-17534-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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