Volume IV-2/W5
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 357-364, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-357-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W5, 357-364, 2019
https://doi.org/10.5194/isprs-annals-IV-2-W5-357-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  29 May 2019

29 May 2019

A FAST VOXEL-BASED INDICATOR FOR CHANGE DETECTION USING LOW RESOLUTION OCTREES

J. Gehrung1,2, M. Hebel1, M. Arens1, and U. Stilla2 J. Gehrung et al.
  • 1Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, 76275 Ettlingen, Germany
  • 2Photogrammetry and Remote Sensing, Technische Universitaet Muenchen, 80333 Muenchen, Germany

Keywords: Change Detection, Local Deformation Analysis, Volumetric Environment Representation

Abstract. This paper proposes a change detection approach that uses a low-resolution octree enhanced with Gaussian kernels to describe free and occupied space. This so-called Gaussian Occupancy Octree is derived from range measurements and used to represent spatial information for a single epoch. Changes between epochs are encoded using a Delta Octree. A qualitative and quantitative evaluation of the proposed approach shows that its advantages are a fast runtime and the ability to make a statement about the re-exploration of space. An evaluation of the classification accuracy shows that our approach tents towards correct classifications with an overall accuracy of 51.5 %, but is also systematically biased towards the appearance of occupied space.