A review on urban traffic cameras: video image processing techniques and applications

Nowadays, cities face severe problems related to traffic management and mobility in general. Therefore, technologies have been developed that can handle these situations and somehow mitigate the caused impact, such as CCTV cameras. However, the techniques for analyzing the images collected by these cameras are increasingly complex and have numerous applications, being dispersed in the literature. Therefore, this article fills an important research gap by presenting a systematic review of the literature on the possible applications of data collected from CCTV cameras and the image analysis and processing techniques that have been developed and proposed in recent years. This systematic review followed the PRISMA statement guidelines and checklist, and three databases were searched, namely Scopus, Web of Science, and Inspec. From the analysis performed, the following applications were identified: image/video analysis and traffic estimation, pedestrian detection, traffic data analysis, and forecasting, and traffic management. Regarding the image analysis and processing techniques YOLO (only look once), GMM (Gaussian mixture method), morphological methods, fuzzy logic, and other proprietary methods stand out. After a thorough analysis of traffic data, most works still implemented relatively trivial traffic management systems to generate a series of actions to be eventually applied to traffic controllers. Additionally, it was realized that these techniques could be implemented in industrial products from a future perspective.