Least squares fitting is a mathematical approach used to find the best-fitting curve or line for a set of data points by minimizing the sum of the squares of the vertical distances (residuals) between the observed values and the values predicted by the model. This technique is widely used in shape matching and registration to accurately align shapes or geometric figures based on data points, ensuring that the differences between corresponding points are minimized.
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