| 摘要 |
An image sequence derived from area surveillance is considered as a collection of independent time series, each of which describes an image feature that summarizes a small neighborhood of the image. These time series are regarded as samples from some underlying distribution, and statistical techniques are used to identify the density function of this distribution. The background can then be identified as a feature of this distribution, moreover the distribution of features in subsequent image frames can be monitored to see if it deviates sufficiently from the current distributions to indicate a change in the background.
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