Model retrieval based on point cloud encoding of airborne lidar

Jyun Yuan Chen, Po Chi Hsu, Chao-Hung Lin

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

Many building models are available in the internet. Based on the concept of data reuse, we propose a system to retrieve models whose shapes are similar to that of point clouds. To consistently encode building models and point clouds, a novel encoding approach is introduced. Our approach can not only encode polygon models but also can handle unorganized, noisy, and incomplete point clouds. In addition, to ease of encoding problem suffering from incomplete data, we propose a resampling technique for point clouds. The experimental results show that our approach can solve the inherent problems of point clouds, i.e., unorganized, noisy and incomplete, and can encode the 3D shape consistently.

Original languageEnglish
Pages4711-4713
Number of pages3
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany
Duration: 2012 Jul 222012 Jul 27

Other

Other2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
CountryGermany
CityMunich
Period12-07-2212-07-27

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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