Motion Trajectory Aggregation Model of Playing Field Based on Spatial Temporal Features

Abstract

Volleyball athletes playing filed motion trajectory aggregation model refers to a group of movement patterns of the volleyball athletes on the playing field, which is usually used to predict the abnormal phenomenon that is occurred in the model. It is difficult for the existing research method to conduct mining on the specific aggregation model accurately and highly efficiently. For this purpose, a kind of athlete trajectory aggregation model mining method based on the spatial temporal features is put forward, which first makes the analysis on the trajectory data by the improved method of Spatial clustering algorithm (SPC), so as to obtain the playing field motion trajectory clustering; Then, by the application of the spatial temporal feature model to replace the method of separate storage for the trajectory data, to carry out real-time observation on the spatial and temporal variation features of the playing field motion trajectory clustering. Experimental results show that, the proposed method is significantly superior to other methods in view of the accuracy and efficiency for the mining of volleyball athlete trajectory aggregation model.