Plane Fitting on Airborne Laser Scanning Data Using RANSAC
نویسندگان
چکیده
Model fitting refers to problem that computing the most ideal parameters of a model so that the model gives the greatest extent of coincidence with the data. The most widely used method for fitting data with Gaussian noises should be ordinary least squares. However, the ordinary least squares method treats each datum equally, which makes it unsuitable for fitting the data containing outliers. Thus, a more robust method is needed this case (Szeliski 2010).
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