基于OpenCV的深度学习目标检测与跟踪

Deep Learning Target Detection and Tracking Based on OpenCV

目标检测和跟踪在工业应用中占有较大的比重,通过目标识别技术,可以快速准确的检验产品的一致性,降低工人劳动强度,提高企业效益,本文主要介绍了一种开源的计算机视觉库——OpenCV,OpenCV中集成的模块能够减少开发人员工作强度。本文对OpenCV中用于目标检测和跟踪的模块,和这些模块的算法基础进行了简要的介绍,本文还将对OpenCV中提供的DNN深度神经网络模块的相关内容和算法框架进行简要的介绍。

Target detection and tracking occupy a large proportion in industrial applications.Through target recognition technology,product consistency can be quickly and accurately tested,labor intensity is reduced,and enterprise efficiency is improved.This paper mainly introduces an open source computer vision library--OpenCV,the integrated modules in OpenCV can reduce the developer's work intensity.In this paper,the modules for target detection and tracking in OpenCV,and the algorithm basis of these modules are briefly introduced.This paper also briefly introduces the related content and algorithm framework of DNN deep neural network module provided in OpenCV.