Title :
Skeletal graphs for efficient structure from motion
Author :
Snavely, Noah ; Seitz, Steven M. ; Szeliski, Richard
Author_Institution :
Washington Univ., Seattle, WA
Abstract :
We address the problem of efficient structure from motion for large, unordered, highly redundant, and irregularly sampled photo collections, such as those found on Internet photo-sharing sites. Our approach computes a small skeletal subset of images, reconstructs the skeletal set, and adds the remaining images using pose estimation. Our technique drastically reduces the number of parameters that are considered, resulting in dramatic speedups, while provably approximating the covariance of the full set of parameters. To compute a skeletal image set, we first estimate the accuracy of two-frame reconstructions between pairs of overlapping images, then use a graph algorithm to select a subset of images that, when reconstructed, approximates the accuracy of the full set. A final bundle adjustment can then optionally be used to restore any loss of accuracy.
Keywords :
graph theory; image motion analysis; image reconstruction; image thinning; pose estimation; graph algorithm; image motion; image reconstruction; pose estimation; sampled photo collection; skeletal graph; skeletal image set; Computational geometry; Image reconstruction; Image restoration; Internet; Joints; Layout; Robustness; Time measurement; Uncertainty; Video sequences;
Conference_Titel :
Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-2242-5
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2008.4587678