Abstract
In order to facilitate the storage, visualization and data mining of large-scale trajectory information, an improved adaptive fitting algorithm of trajectory information is proposed, which can automatically select the optimal fitting interval and generate the key points and coefficients of the fitted interval. The algorithm consists of two steps: Firstly, the adaptive fitting method is used to fit the trajectory points to obtain the most suitable fitted trajectory interval, and the fitting method adopts the least squares method. Secondly, the constrained quadratic programming method is used to optimize the obtained trajectory interval coefficients to make the fitting curve smooth and continuous. The experimental simulation proves that the algorithm has obvious effects on data compression and feature extraction of trajectory information.
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