An image sequence moving straight-line tracking method based on the forecasting mechanism of a point and straight-line optical flow is proposed for the problem of moving straight-line feature tracking in image sequences that contain a complex scene. The basic constraint equation of the point and straight-line optical flow is defined; the equation is derived from the image straight-line expression. The three significant corollaries about the corresponding relationship between the point and straight-line optical flow are deduced based on the basic constraint equation of the point and straight-line optical flow. Then

with the corresponding relationship between the point and straight-line optical flow

straight-line optical flow is estimated with the defined computing model through the mean filtering strategy. With the estimated straight-line optical flow

the moving straight line can be extracted by the given straight-line optical flow threshold. Finally

with the extracted moving straight line and the estimated straight-line optical flow

the prediction coordinate of the moving straight-line in the next frame is obtained. The moving straight-line tracking result is acquired by comparing and selecting the minimum Euclidean distances between the moving straight-line prediction coordinate and the actual coordinates of the next frame in the neighborhood window of the Hough space. To demonstrate the performance of the proposed method in moving straight-line tracking

three elaborate synthetic and real image sequence experiments are conducted. In the experiments

the effects of optical flow estimation

straight-line optical flow threshold

and size of the straight-line matching window are demonstrated. Experimental results show thatthe proposed method can accurately extract and track the moving straight-line; it can also track and match the moving straightline stably. No wrong matching is noted for the interference straight lines of the straight-line tracking result

and the time consumption of the straight-line tracking method is not more than 12 s. Compared with traditional moving straight-line tracking and matching methods

the proposed method has higher straight-line tracking accuracy and better robustness; this condition indicates that the proposed method is more applicable to the problem of moving straight-line tracking in complex scenes.