Iterative Computation of Camera Paths

This paper presents a novel algorithm to iteratively compute camera paths of long image sequences. Scale Invariant Features are first extracted from the ordered set of images. These images are then matched pair-wise sequentially and correspondences are computed. An initial geometric path can be found after by applying a bundle adjustment algorithm on these correspondences. Distances between cameras can be computed from this initial estimation. The iteration process starts by grouping nearby cameras and then bundle adjusting the groups, and ends by merging the groups. This process is repeated until the reprojection errors fall into the preset tolerance. The key point in this algorithm is to take the advantages of loopbacks in the image sequences. We have obtained excellent results for two particular camera paths, namely the spiral path and the snake like path. Our algorithm achieves both precise and stable results.