残差一致性的距离图像分割与拟合

Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Pub Date : 1992-06-15 DOI:10.1109/CVPR.1992.223208

Xinming Yu, T. D. Bui, A. Krzyżak

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引用次数: 1

摘要

作者随机选取合适的距离图像点，求解由这些点确定的方程，求出所选原始类型的参数。从K个样本中，他们测量残差一致性，以选择一组样本点，确定一个方程，该方程最适合当前处理区域中最大的均匀表面斑块。残差一致性通过压缩直方图方法测量，该方法适用于各种噪声水平。为了避免进一步的计算，从处理区域中提取出估计的表面斑块。采用遗传算法提高搜索速度。

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Range image segmentation and fitting by residual consensus

The authors randomly sample appropriate range image points and solve equations determined by these points for the parameters of selected primitive type. From K samples they measure residual consensus to choose one set of sample points that determines an equation having the best fit for the largest homogeneous surface patch in the current processing region. The residual consensus is measured by a compressed histogram method that works at various noise levels. The estimated surface patch is extracted out of the processing region to avoid further computation. A genetic algorithm is used to accelerate the search speed.<>

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Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition

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