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Multi-view Feature Matching and Image Grouping from Multiple Unordered Wide-Baseline Images

  • Xiuyuan Zeng
  • Heng Yang
  • Qing Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5359)

Abstract

In this paper, we present a photo grouping method in multi-view feature matching problem, especially from multiple unordered wide-baseline images. By analyzing and comparing the connections between images with undirected weighted graph, we abstract the photo grouping into a nonlinear optimization problem and tackle it by using an annealing based method. Additionally, a new high-dimensional feature searching algorithm is also developed to find out the initial features matching number more robustly, which is used to be the measurement of image relativities in the grouping algorithm. Finally, we show the analyses and discussions of the performance of the proposed method and experimental results have proven that the novel approach is more efficient than the traditional ones.

Keywords

Feature Vector Image Pair Feature Match Image Grouping Nonlinear Optimization Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xiuyuan Zeng
    • 1
  • Heng Yang
    • 1
  • Qing Wang
    • 1
  1. 1.School of Computer Science and EngineeringNorthwestern Polytechnical UniversityXi’anP. R. China

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