@article{
 title = {Robust global translations with 1DSfM},
 type = {article},
 year = {2014},
 keywords = {Structure from Motion,robust estimation,translations problem},
 pages = {61-75},
 volume = {8691 LNCS},
 id = {bc83b039-1d0c-38a1-b0d5-44f0372d7fc1},
 created = {2022-09-19T09:01:26.025Z},
 file_attached = {true},
 profile_id = {276016a7-2c9d-3507-8888-093db7c54774},
 group_id = {5ec9cc91-a5d6-3de5-82f3-3ef3d98a89c1},
 last_modified = {2022-09-19T09:03:10.093Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {02fb5526-03ff-44ad-8d5c-42bd496c3100},
 private_publication = {false},
 abstract = {We present a simple, effective method for solving structure from motion problems by averaging epipolar geometries. Based on recent successes in solving for global camera rotations using averaging schemes, we focus on the problem of solving for 3D camera translations given a network of noisy pairwise camera translation directions (or 3D point observations). To do this well, we have two main insights. First, we propose a method for removing outliers from problem instances by solving simpler low-dimensional subproblems, which we refer to as 1DSfM problems. Second, we present a simple, principled averaging scheme. We demonstrate this new method in the wild on Internet photo collections. © 2014 Springer International Publishing.},
 bibtype = {article},
 author = {Wilson, Kyle and Snavely, Noah},
 doi = {10.1007/978-3-319-10578-9_5},
 journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
 number = {PART 3}
}

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