Feature detection on 3D face surfaces for pose normalisation and recognition

@article{Maes2010FeatureDO,
  title={Feature detection on 3D face surfaces for pose normalisation and recognition},
  author={Chris Maes and Thomas Fabry and Johannes Keustermans and Dirk Smeets and Paul Suetens and Dirk Vandermeulen},
  journal={2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS)},
  year={2010},
  pages={1-6}
}
This paper presents a SIFT algorithm adapted for 3D surfaces (called meshSIFT) and its applications to 3D face pose normalisation and recognition. The algorithm allows reliable detection of scale space extrema as local feature locations. The scale space contains the mean curvature in each vertex on different smoothed versions of the input mesh. The meshSIFT algorithm then describes the neighbourhood of every scale space extremum in a feature vector consisting of concatenated histograms of shape… CONTINUE READING
Highly Cited
This paper has 115 citations. REVIEW CITATIONS