高维投影空间场景重建的临界超曲面与不稳定性

M. Bertolini, L. Magri
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引用次数: 4

摘要

在多视图几何的背景下,静态场景的图像被建模为从射影空间P^3到射影平面P^2的线性投影,类似地,合适的动态或分段场景的视频或图像可以被建模为从P^k到P^h的线性投影,k>h>=2。在这些设置中,场景的投影重建包括在识别图像之间足够多的对应关系之后,从图像中恢复投影对象和投影本身的位置。重建问题的关键轨迹是在环境空间中点和投影中心的配置,在环境空间中场景的重建失败。关键位点是合适的代数变种。本文研究了高维复射影空间中超曲面的临界轨迹,并确定了它们的方程。此外,为了证明这些临界位点存在的一些实际意义,我们进行了一个模拟实验来测试在临界超表面附近重建场景的不稳定现象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Critical hypersurfaces and instability for reconstruction of scenes in high dimensional projective spaces
In the context of multiple view geometry, images of static scenes are modeled as linear projections from a projective space P^3 to a projective plane P^2 and, similarly, videos or images of suitable dynamic or segmented scenes can be modeled as linear projections from P^k to P^h, with k>h>=2. In those settings, the projective reconstruction of a scene consists in recovering the position of the projected objects and the projections themselves from their images, after identifying many enough correspondences between the images. A critical locus for the reconstruction problem is a configuration of points and of centers of projections, in the ambient space, where the reconstruction of a scene fails. Critical loci turn out to be suitable algebraic varieties. In this paper we investigate those critical loci which are hypersurfaces in high dimension complex projective spaces, and we determine their equations. Moreover, to give evidence of some practical implications of the existence of these critical loci, we perform a simulated experiment to test the instability phenomena for the reconstruction of a scene, near a critical hypersurface.
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来源期刊
Machine Graphics and Vision
Machine Graphics and Vision Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
0.40
自引率
0.00%
发文量
1
期刊介绍: Machine GRAPHICS & VISION (MGV) is a refereed international journal, published quarterly, providing a scientific exchange forum and an authoritative source of information in the field of, in general, pictorial information exchange between computers and their environment, including applications of visual and graphical computer systems. The journal concentrates on theoretical and computational models underlying computer generated, analysed, or otherwise processed imagery, in particular: - image processing - scene analysis, modeling, and understanding - machine vision - pattern matching and pattern recognition - image synthesis, including three-dimensional imaging and solid modeling
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