Gehrung, JoachimJoachimGehrungHebel, MarcusMarcusHebelArens, MichaelMichaelArensStilla, UweUweStilla2022-03-146.6.20192019https://publica.fraunhofer.de/handle/publica/40462710.5194/isprs-annals-IV-2-W5-357-201910.24406/publica-r-4046272-s2.0-85067488972This 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.enChange DetectionLocal Deformation AnalysisVolumetric Environment Representation004670conference paper