Journal
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
Volume 18, Issue 8, Pages 1255-1267Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TVCG.2011.263
Keywords
Three-dimensional/stereo scene analysis; object recognition; segmentation; surface fitting
Categories
Funding
- US National Science Foundation (NSF) [IIS-0917286]
- King Abdullah University of Science and Technology [KUS-C1-016-04]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [0917286] Funding Source: National Science Foundation
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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.
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