A Real-Time Distributed Intelligent Traffic Video-Surveillance System on Embedded Smart Cameras

A real-time video-surveillance system on embedded smart cameras is presented aiming at a wide range of traffic surveillance and monitoring scenarios, in which event detection, vehicle identification and tracking are implemented in front-end cameras. In addition, the proposed system transmits the feature information and related video data of events instead of the complete video data, which greatly reduces the usage rate of network bandwidth on video streaming. A demo system with overall architecture and simplified components was implemented. The algorithms, which were used to detect, identify and track vehicles, employed in the demo system include video foreground subtraction, moving vehicle extraction, color features extraction, etc. The real-time constraint of embedded device used in the experiment renders most complex algorithms simplified. In average case, the system achieves about 17 frames per second in embedded smart camera.