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利用混合高斯模型进行前景检测的源代码实现,依据的是Stauffer发表的Adapptive background mixture models for real-time tracking.-The prospects for the use of Gaussian mixture model, detection of the source code implementation, based on the Stauffer published Adapptive background mixture models for real-time tracking.
Date : 2025-07-01 Size : 5kb User : connie

stauffer的经典的混合高斯模型算法描述,适合做行为检测的人使用。-stauffer the classical Gaussian mixture model algorithm description, suitable for people who use behavior detection.
Date : 2025-07-01 Size : 514kb User : yaotwo

背景建模方法之高斯混合模型,使用到MOG2。算法快,并且可以进行阴影检测。遍历性:对每一个像素进行建模。作者为Z.Zivkovic-The algorithm similar to the standard Stauffer&Grimson algorithm with additional selection of the number of the Gaussian components based on: "Recursive unsupervised learning of finite mixture models " Z.Zivkovic, F.van der Heijden The code is very fast and performs also shadow detection. Number of Gausssian components is adapted per pixel.
Date : 2025-07-01 Size : 10kb User : HH

DL : 0
My implementation of Stauffer & Grimson's GMM(Background subtraction Drawbacks of Stauffer & Grimson's GMM Since its pixel based model fitting, a) lots of unwanted small blobs are scattered all over the frame. e.g. UCSD demo b) main blobs aren't completely foreground. e.g. CVC, Barcelona Univ demo)
Date : 2025-07-01 Size : 26kb User : hamed tirandaz
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