Shape estimation from 3D point clouds

Jingyong Su, Lin Lin Tang

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

Abstract

The problem of estimating a shape in a 3D point cloud data is important due to its general applicability in image analysis, computer vision, and graphics. It is challenging because the data is typically noisy, cluttered, partly missing and unordered. We address shape estimation using a template object under a fully statistical model, where the data is assumed to be modeled using a Poisson process on the object’s boundary (surfaces), corrupted by additive noise and a clutter process. Using analytical likelihood function dictated by the model, we optimize over pose and scale associated with hypothesized templates and estimate most likely shapes in observed point clouds under given shape hypotheses. We demonstrate this framework using examples of 2D and 3D shape estimation in simulated and real data.

Original languageEnglish
Title of host publicationIntelligent Data Analysis and Its Applications - the 1st Euro-China Conference on Intelligent Data Analysis and Applications, Proceeding
EditorsVaclav Snasel, Ajith Abraham, Emilio S. Corchado, Shyue-Liang Wang, Jeng-Shyang Pan, Jeng-Shyang Pan
PublisherSpringer-Verlag
Pages39-46
Number of pages8
ISBN (Electronic)9783319077758
DOIs
StatePublished - 2014
Event1st Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2014 - Shenzhen, China
Duration: Jun 13 2014Jun 15 2014

Publication series

NameAdvances in Intelligent Systems and Computing
Volume297
ISSN (Print)2194-5357

Conference

Conference1st Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2014
CountryChina
CityShenzhen
Period06/13/1406/15/14

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  • Cite this

    Su, J., & Tang, L. L. (2014). Shape estimation from 3D point clouds. In V. Snasel, A. Abraham, E. S. Corchado, S-L. Wang, J-S. Pan, & J-S. Pan (Eds.), Intelligent Data Analysis and Its Applications - the 1st Euro-China Conference on Intelligent Data Analysis and Applications, Proceeding (pp. 39-46). (Advances in Intelligent Systems and Computing; Vol. 297). Springer-Verlag. https://doi.org/10.1007/978-3-319-07776-5_5