Based on projective geometry, a relationship between the moving cameras in the presence of a strong parallax is analyzed, and unique constraints are proposed based on surface homography model. Generally, previous works focus on Planar + Parallax or simple geometric constraints such as fundamental matrix, but the degradation cannot be solved. A much more strong constraint is proposed to modify the surface degradation based on fundamental matrix to line degradation based on surface homography, and solves the degradation by modeling, learning and detecting. Unlike previous works, main planar is not needed and degradation is not ignored with no reason, through surface homography model and modeling-learning-detecting framework. Experiments are performed based on actual image data, and the results show that this model can learn the motion of cameras efficiently and be practical on moving target detection with a moving camera with a strong parallax.