Mutual mapping between surveillance video and 2D geospatial data

被引:0
作者
Zhang, Xingguo [1 ]
Liu, Xuejun [2 ]
Wang, Sining [2 ]
Liu, Yang [2 ]
机构
[1] College of Urban and Environmental Science, Xinyang Normal University, Xinyang
[2] Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing
来源
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2015年 / 40卷 / 08期
基金
中国国家自然科学基金;
关键词
2D geospatial data; GIS; Mapping; Surveillance video;
D O I
10.13203/j.whugis20130817
中图分类号
学科分类号
摘要
In order to achieve the mutual enhancement between surveillance videos and 2D geo-spatial data, a modal including geometric and content mapping is proposed. Firstly, based on the pin-hole camera model of photogrammetry and computer vision, we assume the ground is composed of multiple planes and propose a mapping model. The mapping model has clear physical meaning, convenient and flexible. Through the model, the videos and 2D geospatial data can be mutually projected. Secondly, because the true ground is not flat, undulation has an impact on the mapping between videos and 2D geospatial data, a formula for the impact is provided. Thirdly, the objects in videos are larger nearby and smaller at far distances. In order to get the real space of each pixel, we propose an indicator, video spatial resolution and discuss the spatial distribution. The model is suitable for multiple planes but not suitable for complex geographic scenes.
引用
收藏
页码:1130 / 1136
页数:6
相关论文
共 12 条
[1]  
Kong Y., Design of GeoVideo Data Model and Implementation of Web-based Video GIS, Geomatics and Information Science of Wuhan University, 35, 2, pp. 133-137, (2010)
[2]  
Han Z., Zeng M., Kong Y., Design and Implementation of the Campus Geovideo Monitoring WebGIS System, Science of Surveying and Mapping, 37, 1, pp. 195-197, (2012)
[3]  
Wang Y., Research on Automatic Positioning Techniques for Forest Fire Video Monitoring System Based on GIS, (2008)
[4]  
Bradshaw K.J., Reid I.D., Murray D.W., Et al., The Active Recovery of 3D Motion Trajectories and Their Use in Prediction, IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 3, pp. 219-234, (1997)
[5]  
Coifman B., Beymer D., McLauchlan P., Et al., A Real-time Computer Vision System for Vehicle Tracking and Traffic Surveillance, Transportation Research Part C: Emerging Technologies, 6, 4, pp. 271-288, (1998)
[6]  
Kim K., Oh S., Lee J., Et al., Augmenting Aerial Earth Maps with Dynamic Information, The 8th IEEE International Symposium on Mixed and Augmented Reality, (2009)
[7]  
Song H., Liu X., Lv G., Et al., Real-time Monitoring for the Regional Crowds Status, Journal of Geo-Information Science, 14, 6, (2012)
[8]  
Liu Y., Zhang Z., Zhang J., A New Method for Building Reconstruction Based on Vector Map and Non-metric Camera Image, Geomatics and Informaiton Science of Wuhan University, 30, 2, pp. 146-149, (2005)
[9]  
Jiang W., Design and Implementation of Development Platform for Video Surveillance, (2008)
[10]  
Zhang X., Liu X., Song H., Video Surveillance GIS: A Novel Application, Geoinfomatics 2013, (2013)