The invention discloses a rotary model-based quasi dense corresponding point matching diffusion method. The method mainly comprises the following steps of: for a pair of fisheye images shot in the same scene from different positions, extracting and matching characteristic points in the images, and then accurately positioning the characteristic points, wherein the characteristic points are used as initial seed points; and performing quasi dense corresponding point diffusion from the optimal seed points to the neighborhood, wherein the diffused corresponding points are used as new seed points for subsequent continuous diffusion. In the method, a rotary conversion model is adopted for parallax constraints of the corresponding points, and compared with the conventional affine transformation model, the model is simple in calculation and has only one free parameter, so the whole diffusion process is stable and reliable and can meet most application requirements. In addition, the method is a non-constraint diffusion method, does not need to demarcate the motion parameters of a camera in advance, and has high flexibility. Experimental results verify the feasibility of the method, and the method has strong practicability.