Spatio-Temporal Visual Analysis for Urban Traffic Characters Based on Video Surveillance Camera Data

ISPRS International Journal of Geo-Information

Chong Jiang¹  Haochen Zou²  Keyan Cao³ 

[1] Department of Sport Education and Humanity, Nanjing Sport Institute, Nanjing 210014, China;Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC H3G1M8, Canada;School of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China;

关键词: spatio-temporal visualization;    visual analysis;    traffic pattern;    large scale geospatial;    spatial data mining;   

DOI  :  10.3390/ijgi10030177

来源: DOAJ

【 摘 要 】

Urban road traffic spatio-temporal characters reflect how citizens move and how goods are transported, which is crucial for trip planning, traffic management, and urban design. Video surveillance camera plays an important role in intelligent transport systems (ITS) for recognizing license plate numbers. This paper proposes a spatio-temporal visualization method to discover urban road vehicle density, city-wide regional vehicle density, and hot routes using license plate number data recorded by video surveillance cameras. To improve the accuracy of the visualization effect, during data analysis and processing, this paper utilized Internet crawler technology and adopted an outlier detection algorithm based on the Dixon detection method. In the design of the visualization map, this paper established an urban road vehicle traffic index to intuitively and quantitatively reveal the traffic operation situation of the area. To verify the feasibility of the method, an experiment in Guiyang on data from road video surveillance camera system was conducted. Multiple urban traffic spatial and temporal characters are recognized concisely and efficiently from three visualization maps. The results show the satisfactory performance of the proposed framework in terms of visual analysis, which will facilitate traffic management and operation.

【 授权许可】

Unknown