3D building model retrieval for point cloud modeling

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Based on the concept of data reuse and data sharing, a 3D building model retrieval approach is proposed to reconstruct point clouds for cyber city modeling and updating. Thanks to age of Web 2.0, an increasing number of models are available on the website like Google Warehouse. A huge database with a great diversity can be easily constructed from the open sources of these platforms. We aim to build a 3D building model search engine for the demand of following application such as quick modeling instead of those with large time-consuming. Spherical harmonics function is chosen as the shape-descriptor to parameterize the models in low frequency domain. The most similar model can be extracted by matching the parameterized spherical harmonic coefficients between models and input data. Point cloud data obtained by airborne LiDAR is inputted as query to search the similar models from database. Properties of point cloud data with incompleteness and noise is also a challenge to this research. A set of data preprocessing procedures will be executed to optimize the retrieval result. The experiment results show the possibility and flexibility of proposed algorithm to effectively retrieve the fittest model from database.

Original languageEnglish
Title of host publication32nd Asian Conference on Remote Sensing 2011, ACRS 2011
Number of pages6
Publication statusPublished - 2011 Dec 1
Event32nd Asian Conference on Remote Sensing 2011, ACRS 2011 - Tapei, Taiwan
Duration: 2011 Oct 32011 Oct 7

Publication series

Name32nd Asian Conference on Remote Sensing 2011, ACRS 2011


Other32nd Asian Conference on Remote Sensing 2011, ACRS 2011

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications


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