Probabilistic Temporal Inference on Reconstructed 3D Scenes
Author(s)
Schindler, Grant
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Abstract
Modern structure from motion techniques are capable
of building city-scale 3D reconstructions from large image
collections, but have mostly ignored the problem of large-scale
structural changes over time. We present a general
framework for estimating temporal variables in structure
from motion problems, including an unknown date for each
camera and an unknown time interval for each structural element.
Given a collection of images with mostly unknown or
uncertain dates, we use this framework to automatically recover
the dates of all images by reasoning probabilistically
about the visibility and existence of objects in the scene. We
present results on a collection of over 100 historical images
of a city taken over decades of time.
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Date
2010
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Text
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Post-print
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