Fujitsu Develops Traffic-Video-Analysis Technology Based on Image Recognition and Machine Learning
Fujitsu Laboratories and Fujitsu Research and Development Center have jointly developed a technology that utilizes image processing and machine-learning to analyze surveillance camera images of traffic, with high accuracy and in real time, to recognize traffic conditions such as congestion and accidents. High-precision traffic-video analysis is achieved by combining two technologies.
The first technology analyzes the images from surveillance cameras installed along highways and streets, automatically groups characteristics that can lead to recognition errors, such as changes in lighting and environmental factors including night and fog. The technology also analyzes images from cameras that have been similarly positioned.
The second is a technology analyzes moving objects, such as vehicles and people, and identifies complex incidents such as accidents, while minimizing computational demands.
In field trials of this technology conducted in cities around China in collaboration with the Tsingha University Suzhou Automobile Research Institute (TSARI), Fujitsu found that 11 types of incidents of interest, such as traffic accidents and violations, were recognized with accuracy levels of 90-95%.
This technology can be used to deliver a highly accurate, low-cost monitoring system that can automatically assess traffic conditions, apply traffic-flow controls and analysis to reduce congestion, and take quick action in response to accidents and traffic violations.
Fujitsu Laboratories and Fujitsu Research and Development Center are working to increase the accuracy and incidents recognizable with this technology, and plan to continue field trials jointly with TSARI.