3D reconstruction of dynamic textures in crowd sourced data

Dinghuang Ji, Enrique Dunn, Jan Michael Frahm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

We propose a framework to automatically build 3D models for scenes containing structures not amenable for photo-consistency based reconstruction due to having dynamic appearance. We analyze the dynamic appearance elements of a given scene by leveraging the imagery contained in Internet image photo-collections and online video sharing websites. Our approach combines large scale crowd sourced SfM techniques with image content segmentation and shape from silhouette techniques to build an iterative framework for 3D shape estimation. The developed system not only enables more complete and robust 3D modeling, but it also enables more realistic visualizations through the identification of dynamic scene elements amenable to dynamic texture mapping. Experiments on crowd sourced image and video datasets illustrate the effectiveness of our automated data-driven approach.

Original languageEnglish
Title of host publicationComputer Vision, ECCV 2014 - 13th European Conference, Proceedings
Pages143-158
Number of pages16
EditionPART 1
DOIs
StatePublished - 2014
Event13th European Conference on Computer Vision, ECCV 2014 - Zurich, Switzerland
Duration: 6 Sep 201412 Sep 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8689 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th European Conference on Computer Vision, ECCV 2014
Country/TerritorySwitzerland
CityZurich
Period6/09/1412/09/14

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