Description: For complex background environment under fixed camera, the image data captured video images using Gaussian mixture background modeling method implementation foreground/background segmentation, detecting and tracking moving objects. Before foreground detection, the first training background, the background of each image using a Gaussian mixture model to simulate the number of each Gaussian mixture background adaptively. Then in the testing phase, the pixels on the new GMM match, if the pixel value is able to match one of the Gaussian, then that is the background, otherwise considered a prospect. Since the whole process is continuously updated GMM model in the study, so the dynamic context of a certain robustness. Finally, on a tree swing dynamic background foreground detection, achieved good results.
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GMM模型实现
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