Abstract: Gaussian mixture background model is widely used in
moving target detection of the image sequences. However, traditional
Gaussian mixture background model usually considers the time
continuity of the pixels, and establishes background through statistical
distribution of pixels without taking into account the pixels- spatial
similarity, which will cause noise, imperfection and other problems.
This paper proposes a new Gaussian mixture modeling approach,
which combines the color and gradient of the spatial information, and
integrates the spatial information of the pixel sequences to establish
Gaussian mixture background. The experimental results show that the
movement background can be extracted accurately and efficiently, and
the algorithm is more robust, and can work in real time in tracking
applications.