We address the problem of extending the field of view of a photo-an operation we call uncrop. Given a reference photograph to be uncropped, our approach selects, reprojects, and composites a subset of Internet imagery taken near the reference into a larger image around the reference using the underlying scene geometry. The proposed Markov Random Field based approach is capable of handling large Internet photo collections with arbitrary viewpoints, dramatic appearance variation, and complicated scene layout. We show results that are visually compelling on a wide range of real-world landmarks. © 2014 Springer International Publishing.
CITATION STYLE
Shan, Q., Curless, B., Furukawa, Y., Hernandez, C., & Seitz, S. M. (2014). Photo uncrop. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8694 LNCS, pp. 16–31). Springer Verlag. https://doi.org/10.1007/978-3-319-10599-4_2
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