Volume XL-2/W2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W2, 59-64, 2013
https://doi.org/10.5194/isprsarchives-XL-2-W2-59-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W2, 59-64, 2013
https://doi.org/10.5194/isprsarchives-XL-2-W2-59-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Aug 2013

21 Aug 2013

FEATURE-BASED QUALITY EVALUATION OF 3D POINT CLOUDS – STUDY OF THE PERFORMANCE OF 3D REGISTRATION ALGORITHMS

T. Ridene1, F. Goulette2, and S. Chendeb1 T. Ridene et al.
  • 1CITU PARAGRAPHE, Paris 8 University, 2 rue de la Liberté 93526 Saint-Denis Cedex, Paris region, France
  • 2Robotics Lab, Mines ParisTech, 60 Boulevard Saint Michel 75006 Paris, France

Keywords: FBQ-Evaluation, Fuzzy, Binary, ICP, 3D Point Clouds, MMS, DSM

Abstract. The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.