6 May 2009 Rapid self-organizing maps for terrain surface reconstruction
Author Affiliations +
Since their introduction by Kohonen Self Organizing Maps (SOMs) have been used in various forms for purposes of surface reconstruction. They offer robust and fast approximations of manifold data from unstructured input points while being modestly easy to implement. On the other hand SOMs have certain disadvantages when used in a setup where sparse, reliable and spacial unbounded data occurs. For example, airborne Lidar sensors generate a continuous stream of point data while flying above terrain. We introduce modifications of the SOM's data structure to adapt it to unbounded data. Furthermore, we introduce a new variation of the learning rule called rapid learning that is feasible for sparse but rather reliable data. We demonstrate examples where the surroundings of an aircraft can be reconstructed in almost real time.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Niklas Peinecke, Niklas Peinecke, Bernd R. Korn, Bernd R. Korn, } "Rapid self-organizing maps for terrain surface reconstruction", Proc. SPIE 7328, Enhanced and Synthetic Vision 2009, 732807 (6 May 2009); doi: 10.1117/12.818098; https://doi.org/10.1117/12.818098


Aspects of 3D shape reconstruction
Proceedings of SPIE (February 02 2009)
Updates on fuze and SAR modes in RF channel for...
Proceedings of SPIE (April 30 2009)
Measurement of surface topography by remote sensing
Proceedings of SPIE (October 03 1994)

Back to Top