A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Self-Organizing Maps
Introduction to Autonomous Mobile Robots
Introduction to Autonomous Mobile Robots
An Automated Method for Large-Scale, Ground-Based City Model Acquisition
International Journal of Computer Vision
Dynamic Adaptation and Subdivision in 3D-SOM: Application to Surface Reconstruction
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Growing self-reconstruction maps
IEEE Transactions on Neural Networks
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In this paper, we present a new parallel self-organizing technique for three dimensional shape reconstruction for mobile robotics. The method is based on adaptive input data decomposition, parallel shape reconstruction in decomposed clusters using Kohonen Self-Organizing Map, which creates mesh representation of the input data. Afterwards, the sub-maps are joined together and the final mesh is re-optimized. Our method overcomes a problem of fitting one mesh to complex non-continuous shapes like building interiors. The method allows to process unordered data collected by mobile robots. The method is easily paralelizable and gives promising results.