College student management based on machine vision and intelligent monitoring system

This paper combines machine vision and intelligent detection technology to construct a college student management system. In student feature recognition, this paper uses the frustum plane calculation formula to determine the range of the current viewpoint, and then encloses the grid nodes in the form of spherical bounding boxes to eliminate invalid nodes to simplify the loading and rendering of invalid nodes. This article uses the Bresenham algorithm for rasterising vector lines. Then, this paper proposes a dual node evaluation system based on viewpoint distance and node area complexity to refine the nodes. At the same time, this paper adopts an adaptive method to select the repair of cracks. The effectiveness of the method proposed in this paper has been verified through numerical comparative experiments. Copyright © The Author(s) 2023. Published by Inderscience Publishers Ltd.