A spatiotemporal intelligent framework and experimental platform for urban digital twins  

作　　者：Jinxing HU Zhihan LV Diping YUAN Bing HE Wenjiang CHEN Xiongfei YE Donghao LI Ge YANG 

机构地区：[1]Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,China [2]Department of Game Design,Faculty of Arts,Uppsala University,Uppsala SE-75105,Sweden [3]Shenzhen Urban Public Safety and Technology Institute Co.Ltd,Shenzhen 518172,China

出　　处：《Virtual Reality & Intelligent Hardware》2023年第3期213-231,共19页虚拟现实与智能硬件（中英文）

基　　金：Supported by Key R&D Program of the Ministry of Science and Technology (2019YFC0810704);Key R&D Program of Guangdong Province (2019B111102002);Shenzhen Science and Technology Program (KCXFZ202002011007040)。

摘　　要：Backgrounds This work emphasizes the current research status of the urban Digital Twins to establish an intelligent spatiotemporal framework.A Geospatial Artificial Intelligent(GeoAI)system is developed based on the Geographic Information System and Artificial Intelligence.It integrates multi-video technology and Virtual City in urban Digital Twins.Methods Besides,an improved small object detection model is proposed:YOLOv5-Pyramid,and Siamese network video tracking models,namely MPSiam and FSSiamese,are established.Finally,an experimental platform is built to verify the georeferencing correction scheme of video images.Result The MultiplyAccumulate value of MPSiam is 0.5B,and that of ResNet50-Siam is 4.5B.Besides,the model is compressed by 4.8times.The inference speed has increased by 3.3 times,reaching 83 Frames Per Second.3%of the Average Expectation Overlap is lost.Therefore,the urban Digital Twins-oriented GeoAI framework established here has excellent performance for video georeferencing and target detection problems.

关 键 词：Spatiotemporal intelligence Urban digital twins Geographic information system Artificial intelligence Small target detection 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]