A generative model for online depth fusion

Oliver J. Woodford, George Vogiatzis

Research output: Chapter in Book/Report/Conference proceedingConference publication


We present a probabilistic, online, depth map fusion framework, whose generative model for the sensor measurement process accurately incorporates both long-range visibility constraints and a spatially varying, probabilistic outlier model. In addition, we propose an inference algorithm that updates the state variables of this model in linear time each frame. Our detailed evaluation compares our approach against several others, demonstrating and explaining the improvements that this model offers, as well as highlighting a problem with all current methods: systemic bias.
Original languageEnglish
Title of host publicationComputer vision – ECCV 2012
Subtitle of host publication12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, proceedings, Part V
EditorsAndrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, Cordelia Schmid
Place of PublicationBerlin (DE)
Number of pages14
ISBN (Electronic)978-3-642-33715-4
ISBN (Print)978-3-642-33714-7
Publication statusPublished - 2012
Event12th European Conference on Computer Vision - Florence, Italy
Duration: 7 Oct 201213 Oct 2012

Publication series

NameLecture notes in computer science
ISSN (Print)0302-9743


Conference12th European Conference on Computer Vision

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