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Background Subtraction With Video Coding
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DOI：10.1109/LSP.2013.2280138.png)
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The classic Gaussian mixture model is based on the statistical information of every pixel; it is not robust to light changes. Before analysing every pixel in videos, it must be decoded to raw videos. In this letter, the method combining video coding and the Gaussian mixture model together is proposed. We use intra mode and motion vectors to find the foreground macroblock, then add one overhead flag in the compressed video to indicate it. In the decoder, we just decode possible foreground areas and detect moving objects in these areas. In our experiments, we test this method on two datasets, both of them with unique, dynamic, illumination conditions. Results show that the proposed method is effective to detect moving objects and easily assemble to current automated video surveillance systems.
Keyword:
Background subtraction
Gaussian mixture model
motion detection
video coding
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9.6
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1.1W
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1.7W
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