SFM for planar scenes using image derivatives
Traditionally, the structure from motion (SFM) problem has been solved using feature correspondences. This approach requires reliably detected and tracked features between images taken from widespread locations. In this paper, we present a new paradigm to the SFM problem for planar scenes. The novelty of the paradigm lies in the fact that instead of image feature correspondences, only image derivatives are used. We use robust statistics in order to get robust solutions in presence of outliers. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed methods.