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Unconstrained 3D-mesh generation applied to map building

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2004) 3287 241-248
DOI: 10.1007/978-3-540-30463-0_30
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Abstract

3D map building is a complex robotics task which needs mathematical robust models. From a 3D point cloud, we can use the normal vectors to these points to do feature extraction. In this paper, we will present a robust method for normal estimation and unconstrained 3D-mesh generation from a not-uniformly distributed point cloud. © Springer-Verlag 2004.

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APA

Viejo, D., & Cazorla, M. (2004). Unconstrained 3D-mesh generation applied to map building. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3287, 241–248. https://doi.org/10.1007/978-3-540-30463-0_30

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