Inference-Based Surface Reconstruction of Cluttered Environments

K. Biggers, J. Keyser

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

We present an inference-based surface reconstruction algorithm that is capable of identifying objects of interest among a cluttered scene, and reconstructing solid model representations even in the presence of occluded surfaces. Our proposed approach incorporates a predictive modeling framework that uses a set of user-provided models for prior knowledge, and applies this knowledge to the iterative identification and construction process. Our approach uses a local to global construction process guided by rules for fitting high-quality surface patches obtained from these prior models. We demonstrate the application of this algorithm on several example data sets containing heavy clutter and occlusion. © 2012 IEEE.
Original languageEnglish (US)
Pages (from-to)1255-1267
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Volume18
Issue number8
DOIs
StatePublished - Aug 2012
Externally publishedYes

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