The invention discloses a moving object detection method capable of automatically adapting to complex scenes, which comprises the steps of 1) carrying out illumination compensation on a video image; 2) acquiring a background image of each frame of the video image by using a mixed Gaussian background modeling method; 3) acquiring an absolute difference image of each frame by using a background difference method principle; 4) acquiring an optimal segmentation threshold of a gray probability model of each absolute difference image by adopting a maximum entropy segmentation principle; 5) carrying out binarization processing on each absolute difference image by using the optimal segmentation threshold so as to acquire a foreground image; 6) carrying out morphological processing by adopting modules with different structures; and 7) carrying out region calibration on each foreground image by using a connected domain calibration algorithm, and locking a calibrated moving object by using a rectangular frame. The moving object detection method disclosed by the invention has good moving object adaptive detection accuracy and robustness in different complex scenes such as drastic changes in global illumination, background disturbance, relative movement and the like, and can improve the performance of object detection.