KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS
Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools availab...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2012-07-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B3/91/2012/isprsarchives-XXXIX-B3-91-2012.pdf |
| Summary: | Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In
practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of
modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being
accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and
their representation by the data and the behavior of algorithms to the machine. This “understanding” enables the machine to assist human
interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of
algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing
steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the
advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for
applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our
approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language
(SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists’
knowledge of the scene and algorithmic processing. |
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| ISSN: | 1682-1750 2194-9034 |