RIGID MOTION AND STRUCTURE FROM SEVERAL SETS OF PARALLEL LINES IN A MONOCULAR IMAGE SEQUENCE

An image line is a very reliable feature in the feature-based structure-from-motion (SFM) problem. It has at least three advantages: (1) it is not easily affected by occlusion. (2) It can achieve subpixel accuracy. (3) The correspondence problem is easier and less ambiguous. Although some generalized SFM algorithms using image line features have been recently developed, they usually suffer from high error sensitivity and large matrix size. Besides, in order to make their estimations more robust, many line correspondences (much more than the least requirement in theory) are usually needed. These shortages are not beneficial for practical use. Because many sets of parallel lines are frequently encountered in an artificial 3D environment and can be easily identified, we try to utilize these identified parallel lines to simplify the generalized SFM problem and improve the performance of parameter estimation. A fast and reliable algorithm is proposed in our paper. Both computer-generated and real-world images are tested and several satisfactory results have been obtained. In addition, its error sensitivity and data degeneracy will be discussed.