A fast background scene modeling and maintenance for outdoor surveillance
A fast background scene modeling and maintenance for outdoor surveillance
复制标题
室外监控背景场景快速建模与维护
DOI：
10.1109/icpr.2000.902890
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
L. Davis
中科院分区：
文献类型：
--
作者：
I. Haritaoglu;D. Harwood;L. Davis
我们描述了快速背景场景建模和维护技术的真实的时间视觉监控系统跟踪人在户外环境。它对单目灰度视频图像或红外摄像机的视频图像进行操作。该系统使用形状和运动线索来统计地学习和建模背景场景以检测前景对象，即使背景不是完全静止的（例如树枝的运动）。此外，提出了一种背景维护模型，用于防止误报，例如照明变化（太阳被云阻挡，导致亮度变化），或误报，例如物理变化（当人从停放的汽车中出来时进行检测）。实验结果证明了算法的鲁棒性和实时性。
We describe fast background scene modeling and maintenance techniques for real time visual surveillance system for tracking people in an outdoor environment. It operates on monocular gray scale video imagery or on video imagery from an infrared camera. The system learns and models background scene statistically to detect foreground objects, even when the background is not completely stationary (e.g. motion of tree branches) using shape and motion cues. Also, a background maintenance model is proposed for preventing false positives, such as, illumination changes (the sun being blocked by clouds causing changes in brightness), or false negative, such as, physical changes (person detection while he is getting out of the parked car). Experimental results demonstrate robustness and real-time performance of the algorithm.