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Method and apparatus for foreground segmentation of video sequences

机译:视频序列的前景分割方法和装置

摘要

The present invention relates to a method and system for foreground segmentation in which frames of a video sequence are analyzed in the transform domain to determine one or more features. The features are used to model the background. The background can be modeled as a single Gaussian model with a mean and variance of the features. A current frame is segmented by determining if one or more features of the current frame analyzed in the foreground domain satisfy a threshold between the background model. The threshold value can be based on the mean and/or variance of features. During the segmentation, the mean and variance can be updated based on previous corresponding values and current features to adaptively update the background model. In one embodiment, the frames are divided into a plurality of blocks. A transform is used to analyze the blocks in the transform domain. For example, the transform can be a discrete cosine transform (DCT). The features can be a DC feature comprising the DC coefficient and an AC feature comprising a weighted sum of the AC coefficients. The weighted sum is determined with weights which are varied to emphasize different aspects of the present invention. Additional processing steps can be used to remove false positives, handle sudden global illumination changes, handle sudden local illumination changes and remove false negatives.
机译:本发明涉及一种用于前景分割的方法和系统,其中在变换域中分析视频序列的帧以确定一个或多个特征。这些功能用于对背景建模。可以将背景建模为具有特征均值和方差的单个高斯模型。通过确定在前景域中分析的当前帧的一个或多个特征是否满足背景模型之间的阈值来对当前帧进行分段。阈值可以基于特征的平均值和/或方差。在分割期间,可以基于先前的对应值和当前特征来更新均值和方差,以自适应地更新背景模型。在一实施例中,帧被分为多个块。转换用于分析转换域中的块。例如,该变换可以是离散余弦变换(DCT)。这些特征可以是包括DC系数的DC特征和包括AC系数的加权和的AC特征。用加权来确定加权和,加权被改变以强调本发明的不同方面。可以使用其他处理步骤来消除误报,处理突然的全局照明变化,应对突然的局部照明变化并消除误报。

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