The issue of optimal motion and structure estimation from monocular image sequences with a rigidity scene is addressed. The method has the following characteristics: the dimension of the search space in the nonlinear optimization is drastically reduced by exploiting the relationship between structure and motion parameters; the degree of reliability of the observations and estimates is effectively taken into account; the proposed formulation allows arbitrary interframe motion; and the information about the structure of the scene, acquired from previous images, is systematically integrated into the new estimations. It is shown that any scale factor associated with two consecutive images in a monocular sequence is determined by the scale factor of the first two images. The simulations and experiments with long image sequences of real world scenes indicate that the optimization method developed greatly reduces the computational complexity and substantially improves the motion and structure estimation over that produced by linear algorithms. >
['Ning Cui', 'Juyang Weng', 'Paul Cohen']
Extended structure and motion analysis from monocular image sequences