In this workshop, participants explored and realized the scientific exploration and analysis of Tongji University campus by using multi-dimensional imagery data, GIS and deep learning technology.
In recent years, with the rapid development of deep learning technology and computer vision, the analysis of emerging cities based on imagery data has emerged continuously. However, most of the traditional research focuses on open source data such as commercial street scenes and general resolution remote sensing images because of the limited use of imagery data. Students collected more detailed, real-time and complete data for Tongji campus by using mobile sensing and fixed sensing sensor equipment, and made a systematic analysis by combining different algorithm models of computer vision, including the evaluation of low-carbon renovation of campus building roofs and facades based on drones, the correlation between campus walking environment and its relaxation effect, the campus space vitality modeling of outdoor environment and crowd tracking, and the evaluation of campus mobile phone screen exposure perception through wearable cameras.
In the first half of the workshop, the instructors introduced the application of various sensor devices to the participants, including GoPro (mobile sensing), wearable camera (mobile/fixed mixed sensing), hunting camera (fixed sensing) and unmanned aerial vehicle (aerial sensing), and shared and introduced the relevant research results of BCL, so that the students had a deeper understanding of how to use imagery data for research.
In the second half of the workshop, under the guidance of the instructor, the students used QGIS and other software to make spatial statistics on the acquired data, and identified and scanned the previously acquired image data through algorithms such as Pspnet/Maskrcnn/Yolo (Image Segmentation, Detection and Classification), and made several rounds of reports and discussions on the research topics and progress, thus gaining a basic understanding and practice on how to use various perceptual modes to obtain new data and research methods.
After participating in this workshop, students have an overall understanding and practical experience on multi-dimensional perception, the relationship between computer vision AI and urban research, and various sensing devices.