Statistical Foundation for Hypothesis Testing of Image Data

Kanatani K.
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引用次数: 5

Abstract

A statistical foundation is given to the problem of hypothesizing and testing geometric properties of image data heuristically derived by Kanatani (CVGIP: Image Understanding54 (1991), 333-348). Points and lines in the image are represented by "N-vectors" and their reliability is evaluated by their "covariance matrices". Under a Gaussian approximation of the distribution, the test takes the form of a χ2 test. Test criteria are explicitly stated for model matching and testing edge groupings, vanishing points, focuses of expansion, and vanishing lines.

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图像数据假设检验的统计基础
统计基础给出了假设和测试图像数据的几何特性的问题,这是由Kanatani (CVGIP: image Understanding54(1991), 333-348)启发式推导出来的。图像中的点和线用“n向量”表示,它们的可靠性由它们的“协方差矩阵”来评估。在分布的高斯近似下,检验采用χ2检验的形式。明确地说明了模型匹配和测试边缘分组、消失点、扩展焦点和消失线的测试标准。
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