Abstract
The need for robots to search the 3D data they have saved is becoming more apparent. We present an approach for finding structures in 3D models such as those built by robots of their environment. The method extracts geometric primitives from point cloud data. An attributed graph over these primitives forms our representation of the surface structures. Recurring substructures are found with frequent graph mining techniques. We investigate if a model invariant to changes in size and reflection using only the geometric information of and between primitives can be discriminative enough for practical use. Experiments confirm that it can be used to support queries of 3D models.
Cite
CITATION STYLE
Bore, N., Jensfelt, P., & Folkesson, J. (2015). Querying 3d data by adjacency graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9163, pp. 243–252). Springer Verlag. https://doi.org/10.1007/978-3-319-20904-3_23
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