2013 | OriginalPaper | Chapter
Data Fusion and 3D Geometric Modeling from Multi-scale Sensors
Authors : Dmitry Tansky, Anath Fischer
Published in: Smart Product Engineering
Publisher: Springer Berlin Heidelberg
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
The past several decades have seen major advances in sensor technologies, including surface scanning at multi-scales. While state-of-the-art research focuses on methods for integrating diverse scanned data into a single geometric model for inspection analysis, these methods still cannot handle multi-scale data. This paper proposes a new approach for data fusion from multi-scale sensors by defining two generic frameworks for data fusion: Single-Level Multi-Sensor (SLMS) for multi-scale data merged on one level and Hierarchical Multi-Sensor (HMS) for hierarchically merged multi-scale data. These frameworks are based on state-of-the-art generic frameworks and use the properties of multi-scale sensors properties. The feasibility of the proposed approach is demonstrated on 2.5D surfaces scanned by CMM touch probes and laser scanners and on 3D multi-scale synthetic data from CAD models.