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Reliable surface reconstruction from multiple range images

Part of the Lecture Notes in Computer Science book series (LNCS,volume 1064)


This paper addresses the problem of reconstructing an integrated 3D model from multiple 2.5D range images. A novel integration algorithm is presented based on a continuous implicit surface representation. This is the first reconstruction algorithm to use operations in 3D space only. The algorithm is guaranteed to reconstruct the correct topology of surface features larger than the range image sampling resolution. Reconstruction of triangulated models from multi-image data sets is demonstrated for complex objects. Performance characterization of existing range image integration algorithms is addressed in the second part of this paper. This comparison defines the relative computational complexity and geometric limitations of existing integration algorithms.


  • Field Function
  • Range Image
  • Integration Algorithm
  • Point Search
  • Implicit Surface

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.

Supported by EPSRC GR/K04569. ‘Finite Element Snakes for Depth Data Fusion’


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© 1996 Springer-Verlag Berlin Heidelberg

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Hilton, A., Stoddart, A.J., Illingworth, J., Windeatt, T. (1996). Reliable surface reconstruction from multiple range images. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61122-6

  • Online ISBN: 978-3-540-49949-7

  • eBook Packages: Springer Book Archive