Reduced order modeling for physically-based augmented reality

被引：12

作者：

Badias, Alberto ^{[1
]}

Alfaro, Iciar ^{[1
]}

Gonzalez, David ^{[1
]}

Chinesta, Francisco ^{[2
,3
]}

Cueto, Elias ^{[1
]}

机构：

[1] Univ Zaragoza, Aragon Inst Engn Res I3A, Maria de Luna 3, E-50018 Zaragoza, Spain

[2] ENSAM ParisTech, ESI Chair, 155 Blvd Hop, F-75013 Paris, France

[3] ENSAM ParisTech, PIMM Lab, 155 Blvd Hop, F-75013 Paris, France

来源：

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING | 2018年 / 341卷

关键词：

Model order reduction; Data assimilation; Augmented reality; PROPER GENERALIZED DECOMPOSITION; PARAMETER-IDENTIFICATION; 3D RECONSTRUCTION; REDUCTION;

D O I：

10.1016/j.cma.2018.06.011

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this work we explore the possibilities of reduced order modeling for augmented reality applications. We consider parametric reduced order models based upon separate (affine) parametric dependence so as to speedup the associated data assimilation problems, which involve in a natural manner the minimization of a distance functional. The employ of reduced order methods allows for an important reduction in computational cost, thus allowing to comply with the stringent real time constraints of video streams, i.e., around 30 Hz. Examples are included that show the potential of the proposed technique in different situations. (C) 2018 Elsevier B.Y. All rights reserved.

引用

页码：53 / 70

页数：18

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