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聚类差分图像核密度估计前景目标检测

DOI: 10.11834/jig.20091035

Keywords: 核密度估计,聚类,差分图像,前景目标检测

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Abstract:

针对非参数核密度估计学习阶段信息冗余与重复计算,估计阶段的估计错误噪声和计算量大的问题,提出了一种基于聚类分析的差分图像核密度估计前景目标检测算法。该方法在非参数核密度估计的学习阶段基于最大最小聚类原理从原采样全样本中提取那些具有较高频度和多样性的小样本来包含尽可能多的关键样本信息,在估计阶段采用基于自适应阈值的图像差分滤去非典型的运动像素,再利用高斯核密度估计进行运动像素分类。实验结果表明该方法限制了非典型运动像素估计错误产生的噪声,并减少了核密度估计计算量,提高了算法的实时性。

References

[1]  Lo B P L,Velastin S A.Automatic congestion detection system for underground platforms[A].In:Proceedings of International Symposium on Intelligent Multimedia,Video,and Speech Processing[C],Hong Kang,China,2001:158-161.
[2]  Colombari A,Fusiello A,Murino V.Segmentation and tracking of multiple video objects[J].Pattern Recognition,2007,40 (4):1307-1317.
[3]  Stauffer C,Grimson W E L.Adaptive background mixture models for real-time tracking[A].In:Proceedings of the Computer Society on Computer Vision and Pattern Recognition[C],FortCollins,USA,1999:246-252.
[4]  Zivkovic Z.Improved adaptive Gaussian mixture model for backgroud subtraction[A].In:Proceedings of the 17th International Conference on Pattern Recognition[C],Cambridge,United Kingdom,2004:28-31.
[5]  Elgammal A M,Hanvood D,Davis L S.Non-parametric model for background subtraction[A].In:Proceedings of the 6th European Conference on Computer Vision[C],Dublin,Ireland,2000:751-767.
[6]  Mittal A,Paragios N.Motion-based background subtraction using adaptive kernel density estimation[A].In:Proceedings of the Computer Society on Conference on Computer Vision and Pattern Recognition[C],Washington D C,USA,2004:302-309.
[7]  Li L,Huang W,Gu I Y H,et al.Foreground object detection from videos containing complex background[A].In:Proceedings of 11 th ACM Multimedia Conference[C],Berkeley,USA,2003:2-10.
[8]  Ridder C,Munkeh O,Kirohner H.Adaptive background estimation and foreground detection using Kalman-fihering[A].In:Proceedings of the Int\' 1 Conference on Recent Advances Sinmechatronics[C],Istanbul,Turkey,1995:193-199.
[9]  Xu Dong-bin,Huang Lei,Liu Chang-ping.Adaptive Kernel density estimation for motion detection[J].Acta Automatica Sinica.2009,35 (4):379-385.[徐东彬,黄磊,刘昌平.自适应核密度估计运动检测方法[J].自动化学报.2009,35(4):379-385.]
[10]  Rosin P.Thresholding for change detection[A].In:proceedings of IEEE Int\' 1 Conference on Computer Vision[C],Bombay,India,1998:274-279.

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