摘要
近年来,深度学习凭借其在识别应用中超高的预测准确率,在图像处理领域获得了极大关注,这势必提升现有图像处理系统的性能并开创新的应用领域。本文在充分研究深度学习常用模型和技术框架等最新热点前提下,基于树莓派、Arduino这两种嵌入式设备,设计了一款实现物体识别与追踪的智能小车机器人。该智能小车通过搭载在智能小车上的摄像头采集数据,利用计算机视觉的目标识别与追踪模型计算出被跟踪物体的位置信息,在目标物体移动的过程中,通过嵌入式设备分析位置数据计算出控制命令来操控智能小车实现目标跟踪。
In recent years,deep learning has attracted great attention in the field of image processing due to its high prediction accuracy in recognition applications,which is bound to improve the performance of existing image processing systems and create new application fields.On the premise of fully studying the common models and technical frameworks of deep learning and other latest hot spots,this paper designs an intelligent robot car for object recognition and tracking based on two embedded devices,raspberry PI and Arduino.The smart car using cameras to collect data on the smart car,target recognition and tracking using computer vision model to calculate the location information of tracked objects,in the process of moving target object,through the analysis of the embedded devices location data to calculate the control commands to control the smart car to realize target tracking.
作者
耿韶光
GENG Shao-guang(Tianjin Electronic Information College,Tianjin 300350)
出处
《数字技术与应用》
2020年第5期161-162,共2页
Digital Technology & Application
