3D surface registration using Z-SIFT

Lulu He*, Sen Wang, Thrasyvoulos N Pappas

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


We present a Z-SIFT based 3D surface registration algorithm that utilizes the depth information enhanced SIFT features to make initial alignment and the 2D feature weighted Iterative Closest Point (ICP) algorithm to realize accurate registration. The combination of SIFT features and depth information extracts faithful corresponding points between the 2D images and provides good coarse alignment for the 3D surfaces. The 2D feature weighted ICP also outperforms the naive ICP algorithm in terms of speed and accuracy. We use this approach in the context of multiple view alignment for 3D scanners. Experimental results with real objects and human faces indicate the effectiveness of the proposed approach.

Original languageEnglish (US)
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Number of pages4
StatePublished - Dec 1 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: Sep 11 2011Sep 14 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2011 18th IEEE International Conference on Image Processing, ICIP 2011


  • 3D surface registration
  • Z-SIFT
  • weighted iterative closest point

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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