Based on projective geometry, the relation between the moving camera and still scene was analyzed, and a fast estimation algorithm was proposed based on the optical center coordinate system. On this coordinate in which the camera was always static, the scene and the targets were moving instead. The problem of moving target detection on a moving camera was transformed into distinguishing independent movement of targets from the global motion of scenes on a still platform and a concise form of optical flow constraint was deduced. This framework compensated the random movement according to the optical flow field which was got from KLT. Compared with the original algorithm, the computing speed increased about 10 times while ensuring accuracy and robustness. Experiments were performed based on actual image data, and the results show that this model can reduce the computation time extreamly under the premise of ensuring the accuracy and robustness, and be pratical on moving target detection with a moving camera without construction.