A statistical analysis of shape reconstruction from areas of shadows

被引:0
|
作者
Poonawala, A [1 ]
Milanfar, P [1 ]
Gardner, RJ [1 ]
机构
[1] Univ Calif Santa Cruz, Dept Comp Engn, Santa Cruz, CA 95064 USA
来源
THIRTY-SIXTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS - CONFERENCE RECORD, VOLS 1 AND 2, CONFERENCE RECORD | 2002年
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中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We present a statistical analysis of the problem of shape reconstruction from measurements of the brightness function (areas of shadows) by deriving the Cramer-Rao lower bound (CRLB) on the estimated 2D boundary. Confidence region techniques are used to analyze and visualize. the performance of the 2-D parametric shape estimation problem. The brightness function data is very weak, so we have to use a constrained CRLB on the shape parameters to form the confidence regions. Algorithms for reconstructing the shape of a convex object from multiple measurements of its brightness function were developed in [2] and [3]. The Cramer-Rao bound analysis presented here provides statistical estimates that can be used for performance evaluation of these algorithms.
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页码:916 / 920
页数:5
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