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Optimization

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Book cover Motion and Structure from Image Sequences

Part of the book series: Springer Series in Information Sciences ((SSINF,volume 29))

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Abstract

Although the linear algorithm discussed in Chapter 3 is computationally fast, the solution is not optimal in the presence of noise. The methods discussed in this chapter aim at global optimality to significantly improve the accuracy of the solution. First, some situations are identified in which the solution of the linear algorithm is very unstable and thus the optimization is especially crucial. Then, methods for optimal estimation are investigated with two types of noise model: 3-D noise and 2-D image plane noise. A two-step computational approach is introduced for the nonlinear optimization. The first step is computing preliminary solution using a linear algorithm. The second step is iteratively improving this preliminary solution to reach an optimal solution. Then, other related issues are investigated, which include error bound, error estimation, as well as sequential and batch processing techniques.

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Authors and Affiliations

  1. Beckman Institute, University of Illinois at Urbana-Champaign, 405 North Mathews Ave., 61801, Urbana, IL, USA

    Professor Juyang Weng, Professor Thomas S. Huang & Professor Narendra Ahuja

Authors
  1. Professor Juyang Weng
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  2. Professor Thomas S. Huang
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  3. Professor Narendra Ahuja
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© 1993 Springer-Verlag Berlin Heidelberg

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Weng, J., Huang, T.S., Ahuja, N. (1993). Optimization. In: Motion and Structure from Image Sequences. Springer Series in Information Sciences, vol 29. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77643-4_4

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  • DOI: https://doi.org/10.1007/978-3-642-77643-4_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-77645-8

  • Online ISBN: 978-3-642-77643-4

  • eBook Packages: Springer Book Archive

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