caa a22 4500 605541310 CHVBK 20210128100915.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00371-014-1040-4 doi (NATIONALLICENCE)springer-10.1007/s00371-014-1040-4 Interactive partial 3D shape matching with geometric distance optimization [Elektronische Daten] [Michael Martinek, Roberto Grosso, Günther Greiner] In this paper, we propose an efficient method for partial 3D shape matching based on minimizing the geometric distance between the source and the target geometry. Unlike existing methods, our method does not use a feature-based distance in order to obtain a matching score. Instead, we use a fast, GPU-based method to approximate the true geometric distance between the source and the target by rendering the source object into a distance field which was built around the target. This function behaves smoothly in the space of transformations and allows for an efficient gradient-based local optimization. In order to overcome local minima, we use single point correspondences between surface points on the source and the target respectively employing simple, yet efficient local features based on the distribution of normal vectors around a reference point. The best correspondences define starting positions for a local optimization. The high efficiency of the distance computation allows for robust determination of the global minima in less than a second, which makes our method usable in interactive applications. Our method works for any kind of input data since it only requires point data with normal information at each point. We also demonstrate the capability of our algorithm to perform global alignment of similar 3D objects. Springer-Verlag Berlin Heidelberg, 2014 Shape matching nationallicence Partial matching nationallicence Part-in-whole matching nationallicence Object alignment nationallicence Martinek Michael University of Erlangen-Nuremberg, Computer Graphics Group, Erlangen, Germany aut Grosso Roberto University of Erlangen-Nuremberg, Computer Graphics Group, Erlangen, Germany aut Greiner Günther University of Erlangen-Nuremberg, Computer Graphics Group, Erlangen, Germany aut The Visual Computer Springer Berlin Heidelberg 31/2(2015-02-01), 223-233 0178-2789 31:2<223 2015 31 371 https://doi.org/10.1007/s00371-014-1040-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-014-1040-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Martinek Michael University of Erlangen-Nuremberg, Computer Graphics Group, Erlangen, Germany aut NATIONALLICENCE 700 1- Grosso Roberto University of Erlangen-Nuremberg, Computer Graphics Group, Erlangen, Germany aut NATIONALLICENCE 700 1- Greiner Günther University of Erlangen-Nuremberg, Computer Graphics Group, Erlangen, Germany aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/2(2015-02-01), 223-233 0178-2789 31:2<223 2015 31 371