Abstract: To detect moving objects accurately and rapidly from the videos sequences,this paper proposed a novel G-GMM method for automatic detection via combination of GMM and Grabcut techniques in image processing.Firstly,this algorithm uses GMM(Gaussian Mixture Model) based background subtraction to produce binary images for every mo-ving object and then constructs their minimum marking rectangles.And then it follows the image information initialization of each marking rectangle via Grabcut.Finally,an iterative algorithm with foreground parameters is adopted to optimize the object segmentation and thus the moving object contour is obtained.Experimental results indicate that the proposed method achieves good accuracy and robustness in the still camera outdoor video surveillance system,providing promising detection results for both rigid and non-rigid objects.

Key words: Object detection,Grabcut-gaussian mixture model(G-GMM),Foreground motion,Image segmentation