@InProceedings{BrahmachariSark:2011:ViClWi,
author = "Brahmachari, Aveek Shankar and Sarkar, Sudeep",
affiliation = "University of South Florida, Computer Science and Engineering and
University of South Florida, Computer Science and Engineering",
title = "View Clustering of Wide-Baseline N-Views for Photo Tourism",
booktitle = "Proceedings...",
year = "2011",
editor = "Lewiner, Thomas and Torres, Ricardo",
organization = "Conference on Graphics, Patterns and Images, 24. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "Computer Vision, Image Collection, Epipolar Geometry, Photo
Organization.",
abstract = "The problem of view clustering is concerned with finding connected
sets of overlapping views in a collection of photographs. The view
clusters can be used to organize a photo collection, traverse
through a collection, or for 3D structure estimation. For large
datasets, geometric matching of all image pairs via pose
estimation to decide on content overlap is not viable. The problem
becomes even more acute if the views in the collection are
separated by wide baselines, i.e. we do not have a dense view
sampling of the 3D scene that leads to increase in computational
cost of epipolar geometry estimation and matching. We propose an
efficient algorithm for clustering of such many weakly overlapping
views, based on opportunistic use of epipolar geometry estimation
for only a limited number of image pairs. We cast the problem of
view clustering as finding a tree structure graph over the views,
whose weighted links denote likelihood of view overlap. The
optimization is done in an iterative fashion starting from an
minimum spanning tree based on photometric distances between image
pairs. At each iteration step, we rule out edges with low
confidence of overlap between the respective views, based on
epipolar geometry estimates. The minimum spanning tree is
recomputed and the process is repeated until there is no further
change in the link structure. We show results on the images in the
2010 Nokia Grand Challenge Dataset that contains images with low
overlap with each other.",
conference-location = "Macei{\'o}, AL, Brazil",
conference-year = "28-31 Aug. 2011",
doi = "10.1109/SIBGRAPI.2011.43",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2011.43",
language = "en",
ibi = "8JMKD3MGPBW34M/3A3L7LB",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3A3L7LB",
targetfile = "VIEW-CLUSTER_v21.pdf",
urlaccessdate = "2024, Apr. 29"
}