罗志才, 周浩, 钟波, 张坤. Gauss-Jackson积分器算法分析与验证[J]. 武汉大学学报 ( 信息科学版), 2013, 38(11): 1364-1368.
引用本文: 罗志才, 周浩, 钟波, 张坤. Gauss-Jackson积分器算法分析与验证[J]. 武汉大学学报 ( 信息科学版), 2013, 38(11): 1364-1368.
CHANG Qinglong, XIA Hongshan, . Pedestrians Gathering Detection Based on Normalized Foreground and Two-dimension Joint Entropy[J]. Geomatics and Information Science of Wuhan University, 2013, 38(11): 1364-1368.
Citation: CHANG Qinglong, XIA Hongshan, . Pedestrians Gathering Detection Based on Normalized Foreground and Two-dimension Joint Entropy[J]. Geomatics and Information Science of Wuhan University, 2013, 38(11): 1364-1368.

Gauss-Jackson积分器算法分析与验证

Pedestrians Gathering Detection Based on Normalized Foreground and Two-dimension Joint Entropy

  • 摘要: 针对卫星轨道数值积分、变分方程解算等问题,研究了Gauss-Jackson积分器的原理和计算流程,提出了移位重排方式来优化其存储方式的方法,采用开普勒轨道、庞加莱轨道根数、状态转移矩阵等多种参数评估其性能,并与Runge-Kutta、Adams-Cowell等数值积分器进行了比较。计算结果表明,由于对启动点引入中值改正,Gauss-Jackson数值积分器的计算精度高、速度快,可为卫星轨道数值积分和变分方程求解等问题提供稳定、高效的算法。

     

    Abstract: A normalized foreground computing approach based on the camera perspective effect is presented.A two-dimensional probability density for the binary foreground is calculated through classic joint probability distribution theory,and then the two-dimension joint entropy is calculated.Finally,a novel model based on normalized foreground and two-dimension joint entropy for detecting pedestrian gathering is proposed.Experimental results show that this model can quickly and effectively detect a pedestrian gathering event in a surveillance scene.

     

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