The movement of a camera makes the moving objects detection more difficult under a complex background. In order to cope with the dynamically changed background, we propose an object detection method based on the SIFT features match and Motion History Image. Firstly, the feature points are detected by the SIFT algorithm to compute the parameters of the affine transform model, guided by RANSAC, to compensate the global motion between images. Secondly, we adopt the MHI method to detect moving objects. The robustness of the SIFT features match and the validity of picking out the outliers by the  RANSAC algorithm make the parameters of the affine transform model compute accurately, and MHI shows the moving objects and the moving direction of objects clearly. The experimental results demonstrate that our algorithm can detect the moving objects accurately, and show the moving direction of the foreground objects, compared  with the Ninad Thakoor's method.