基于概率密度函数的隐式表示和场景重建

Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) Pub Date : 1999-06-23 DOI:10.1109/CVPR.1999.784604

S. Seitz, P. Anandan

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引用次数: 16

摘要

提出了一种将线性特征表示为二维或三维概率密度函数的方法。这种方法的三个主要优点是:(1)操作点、线和面的统一表示和代数，(2)不确定性信息的无缝结合，以及(3)最大似然形状估计的非常简单的递归解决方案。介绍了非校准仿射场景重建的应用，并给出了室外环境图像的重建结果。

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Implicit representation and scene reconstruction from probability density functions

A technique is presented for representing linear features as probability density functions in two or three dimensions. Three chief advantages of this approach are (1) a unified representation and algebra for manipulating points, lines, and planes, (2) seamless incorporation of uncertainty information, and (3) a very simple recursive solution for maximum likelihood shape estimation. Applications to uncalibrated affine scene reconstruction are presented, with results on images of an outdoor environment.

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Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)

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