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Shape Abstraction through Multiple Optimal Solutions

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Advances in Visual Computing (ISVC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6939))

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Abstract

Shape abstraction is an important problem facing researchers in many fields such as pattern recognition, computer vision, and industrial design. Given a set of shapes, a recently developed shape abstraction framework generates an abstracted shape through the correspondences between their features. The correspondences are obtained based on the optimal solution of a well known transportation problem. Considering the case where multiple optimal solutions exist for one problem, this paper ranks all optimal solutions based on how much they preserve the local neighborhood relations and creates the abstracted shape using the solution with the highest rank. Experimental evaluation of the framework demonstrates that the proposed approach compares favorably with the previous shape abstraction technique.

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Author information

Authors and Affiliations

  1. Computer Engineering Department, TOBB University of Economics and Technology, Sogutozu Cad. No:43, 06560, Ankara, Turkey

    Marlen Akimaliev & M. Fatih Demirci

Authors
  1. Marlen Akimaliev
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  2. M. Fatih Demirci
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Editor information

Editors and Affiliations

  1. University of Nevada, 89557, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, 94035, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, 94720, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, 89512, Reno, NV, USA

    Darko Koracin

  5. Department of Computer Science and Engineering, University of South Carolina, 29208, Columbia, SC, USA

    Song Wang

  6. HRL Laboratories, 3011 Malibu Canyon Road, 90265-4797, Malibu, CA, USA

    Kim Kyungnam

  7. Purdue University, West Lafayette, 47907-2021, IN, USA

    Bedrich Benes

  8. Sandia National Laboratory, 87185, Albuquerque, NM, USA

    Kenneth Moreland

  9. University of Louisiana at Lafayette, 70504, LA, USA

    Christoph Borst

  10. Adobe Systems Incorporated, San Francisco, CA, USA

    Stephen DiVerdi

  11. Polytechnic Institute of NYU, 11201, Brooklyn, NY, USA

    Chiang Yi-Jen

  12. Lawrence Livermore National Laboratory, 94551-0808, Livermore, CA, USA

    Jiang Ming

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© 2011 Springer-Verlag Berlin Heidelberg

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Akimaliev, M., Demirci, M.F. (2011). Shape Abstraction through Multiple Optimal Solutions. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2011. Lecture Notes in Computer Science, vol 6939. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24031-7_59

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  • DOI: https://doi.org/10.1007/978-3-642-24031-7_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24030-0

  • Online ISBN: 978-3-642-24031-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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