基于嵌入式智能摄像头的实时分布式智能交通视频监控系统

X. Lu, C. Ye, Jian Yu, Yaying Zhang
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引用次数: 6

摘要

针对广泛的交通监控场景,提出了一种基于嵌入式智能摄像机的实时视频监控系统,该系统在前端摄像机中实现了事件检测、车辆识别和跟踪。此外,该系统传输事件的特征信息和相关视频数据,而不是完整的视频数据,大大降低了视频流的网络带宽使用率。实现了一个体系结构完整、组件简化的演示系统。在演示系统中采用的检测、识别和跟踪车辆的算法包括视频前景减法、运动车辆提取、颜色特征提取等。实验中使用的嵌入式设备的实时性约束使得大多数复杂的算法得到简化。在嵌入式智能摄像机中,系统平均每秒可达到17帧左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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