Application of 3D Scene Reconstruction in Sports Public Service Based on Pyramid LK Optical Flow Method and RANSAC Algorithm

The ultimate aim of sports community service is to satisfy the growing demand for sports. Competitive sports have developed rapidly in the sports cause, so how to make better use of it to achieve the “feeding” of sports public service has become the focus of research. In this study, color clustering and image local entropy are combined to detect the plane scene, and the preliminary detection results are obtained. Then the foreground pixel is completed by using the target significance information to realize multi-target detection. According to the geometric constraints of the scene, a projection matrix solution method based on global optimization is proposed, and the sequential correlation strategy is applied to match the target points. The proposed model estimates camera motion parameters according to the functional relationship between feature points to realize 3D reconstruction of plane scene sequence. It is verified that the absolute and relative errors of the 3D reconstruction model are 2.11 ㎜ and 0.42%, respectively. The average detection accuracy was 93.88%. It has good stability, applicability and reconstruction effect. The reasonable application of this model can promote the sports and enhance the enthusiasm of the whole people.