TY - JFULL AU - Hu Haibo and Zhao Hong PY - 2010/8/ TI - Real-time Tracking in Image Sequences based-on Parameters Updating with Temporal and Spatial Neighborhoods Mixture Gaussian Model T2 - International Journal of Electrical and Computer Engineering SP - 1037 EP - 1043 VL - 4 SN - 1307-6892 UR - https://publications.waset.org/pdf/9832 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 43, 2010 N2 - 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. ER -