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Proceedings Paper

Automating 3D reconstruction using a probabilistic grammar
Author(s): Hanwei Xiong; Jun Xu; Chenxi Xu; Ming Pan
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Paper Abstract

3D reconstruction of objects from point clouds with a laser scanner is still a laborious task in many applications. Automating 3D process is an ongoing research topic and suffers from the complex structure of the data. The main difficulty is due to lack of knowledge of real world objects structure. In this paper, we accumulate such structure knowledge by a probabilistic grammar learned from examples in the same category. The rules of the grammar capture compositional structures at different levels, and a feature dependent probability function is attached for every rule. The learned grammar can be used to parse new 3D point clouds, organize segment patches in a hierarchal way, and assign them meaningful labels. The parsed semantics can be used to guide the reconstruction algorithms automatically. Some examples are given to explain the method.

Paper Details

Date Published: 8 October 2015
PDF: 5 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 967531 (8 October 2015); doi: 10.1117/12.2202966
Show Author Affiliations
Hanwei Xiong, Guangdong Univ. of Technology (China)
Jun Xu, Guangdong Univ. of Technology (China)
Chenxi Xu, Guangdong Univ. of Technology (China)
Ming Pan, Guangdong Univ. of Technology (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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