# Dense 3-D Structure from Image Sequences Using Probabilistic Depth Carving

Annie Yao, Andrew Calway, Dense 3-D Structure from Image Sequences Using Probabilistic Depth Carving. *Proceedings of the 14th British Machine Vision Conference (BMVC 2003)*. ISBN 1 901725 23 5, pp. 211–220. September 2003. PDF, 304 Kbytes.
## Abstract

We describe an algorithm to determine dense 3-D structure in a static
scene from an image sequence captured by a moving camera. Metric
camera motions are first determined using a recursive structure from
motion algorithm based on tracked feature points. Dense depth
information for a subset of key frames is then obtained using a novel
probabilistic depth carving algorithm - analogous to space
carving - in which depth probabilities obtained locally about the key
frames are combined in 3-D space. An important component in this
process is that opacity and occlusion relationships are modelled
explicitly, enabling consistent combination of the depth
probabilities. Results of experiments on a real sequence illustrate
the effectiveness of the approach.

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