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

A Yao, A Calway

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

16 Citations (Scopus)

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.
Translated title of the contributionDense 3-D Structure from Image Sequences Using Probabilistic Depth Carving
Original languageEnglish
Title of host publicationUnknown
PublisherBMVA 2003
Pages211 - 220
Number of pages9
ISBN (Print)1901725235
Publication statusPublished - Sep 2003

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 14th British Machine Vision Conference (BMVC 2003)

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