Advertisement
Published in:
2015 | OriginalPaper | Chapter
Multi-layer Perceptrons for Voxel-Based Classification of Point Clouds from Natural Environments
Authors : Victoria Plaza, Jose Antonio Gomez-Ruiz, Anthony Mandow, Alfonso Garcia-Cerezo
Published in: Advances in Computational Intelligence
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper addresses classification of 3D point cloud data from natural environments based on voxels. The proposed model uses multi-layer perceptrons to classify voxels based on a statistic geometric analysis of the spatial distribution of inner points. Geometric features such as tubular structures or flat surfaces are identified regardless of their orientation, which is useful for unstructured or natural environments. Furthermore, the combination of voxels and neural networks pursues faster computation than alternative strategies. The model has been successfully tested with 3D laser scans from natural environments.