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Title: Reconstruction of shapes of near symmetric and asymmetric objects

Abstract

A system processes 2D images of 2D or 3D objects, creating a model of the object that is consistent with the image and as veridical as the perception of the 2D image by humans. Vertices of the object that are hidden in the image are recovered by using planarity and symmetry constraints. The 3D shape is recovered by maximizing 3D compactness of the recovered object and minimizing its surface area. In some embodiments, these two criteria are weighted by using the geometric mean.

Inventors:
; ;
Issue Date:
Research Org.:
DOESC (USDOE Office of Science (SC) (United States))
Sponsoring Org.:
USDOE
OSTI Identifier:
1082953
Patent Number(s):
8406567
Application Number:
12/581,604
Assignee:
Purdue Research Foundation (West Lafayette, IN)
DOE Contract Number:  
31-1380-101
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Pizlo, Zygmunt, Sawada, Tadamasa, and Li, Yunfeng. Reconstruction of shapes of near symmetric and asymmetric objects. United States: N. p., 2013. Web.
Pizlo, Zygmunt, Sawada, Tadamasa, & Li, Yunfeng. Reconstruction of shapes of near symmetric and asymmetric objects. United States.
Pizlo, Zygmunt, Sawada, Tadamasa, and Li, Yunfeng. Tue . "Reconstruction of shapes of near symmetric and asymmetric objects". United States. https://www.osti.gov/servlets/purl/1082953.
@article{osti_1082953,
title = {Reconstruction of shapes of near symmetric and asymmetric objects},
author = {Pizlo, Zygmunt and Sawada, Tadamasa and Li, Yunfeng},
abstractNote = {A system processes 2D images of 2D or 3D objects, creating a model of the object that is consistent with the image and as veridical as the perception of the 2D image by humans. Vertices of the object that are hidden in the image are recovered by using planarity and symmetry constraints. The 3D shape is recovered by maximizing 3D compactness of the recovered object and minimizing its surface area. In some embodiments, these two criteria are weighted by using the geometric mean.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2013},
month = {3}
}