research-article

A pipeline for building 3D models using depth cameras

Authors:

Avishek Chatterjee,

Venu Madhav GovinduAuthors Info & Claims

ICVGIP '12: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing

Article No.: 38, Pages 1 - 8

https://doi.org/10.1145/2425333.2425371

Published: 16 December 2012 Publication History

Abstract

In this paper we describe a system for building geometrically consistent 3D models using structured-light depth cameras. While the commercial availability of such devices, i.e. Kinect, has made obtaining depth images easy, the data tends to be corrupted with high levels of noise. In order to work with such noise levels, our approach decouples the problem of scan alignment from that of merging the aligned scans. The alignment problem is solved by using two methods tailored to handle the effects of depth image noise and erroneous alignment estimation. The noisy depth images are smoothed by means of an adaptive bilateral filter that explicitly accounts for the sensitivity of the depth estimation by the scanner. Our robust method overcomes failures due to individual pairwise ICP errors and gives alignments that are accurate and consistent. Finally, the aligned scans are merged using a standard procedure based on the signed distance function representation to build a full 3D model of the object of interest. We demonstrate the performance of our system by building complete 3D models of objects of different physical sizes, ranging from cast-metal busts to a complete model of a small room as well as that of a complex scale model of an aircraft.

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Cited By

Gomes LSilva LBellon O(2018)Exploring RGB-D Cameras for 3D Reconstruction of Cultural HeritageJournal on Computing and Cultural Heritage 10.1145/323067411:4(1-24)Online publication date: 5-Dec-2018
https://dl.acm.org/doi/10.1145/3230674
Govindu V(2016)Motion Averaging in 3D Reconstruction ProblemsRiemannian Computing in Computer Vision10.1007/978-3-319-22957-7_7(145-164)Online publication date: 2016
https://doi.org/10.1007/978-3-319-22957-7_7
Zhang LDong HSaddik A(2015)From 3D Sensing to PrintingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/281871012:2(1-23)Online publication date: 20-Oct-2015
https://dl.acm.org/doi/10.1145/2818710
Show More Cited By

Index Terms

A pipeline for building 3D models using depth cameras
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation
    2. Shape modeling
2. Theory of computation
  1. Randomness, geometry and discrete structures
    1. Computational geometry

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cover image ACM Other conferences

ICVGIP '12: Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing

December 2012

633 pages

ISBN:9781450316606

DOI:10.1145/2425333

Program Chairs:
Bill Triggs
CNRS, France
,
Kavita Bala
Cornell University
,
Sharat Chandran
IIT Bombay, India

Copyright © 2012 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 December 2012

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ICVGIP '12

ICVGIP '12: The Eighth Indian Conference on Vision, Graphics and Image Processing

December 16 - 19, 2012

Mumbai, India

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Overall Acceptance Rate 95 of 286 submissions, 33%

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Cited By

Gomes LSilva LBellon O(2018)Exploring RGB-D Cameras for 3D Reconstruction of Cultural HeritageJournal on Computing and Cultural Heritage 10.1145/323067411:4(1-24)Online publication date: 5-Dec-2018
https://dl.acm.org/doi/10.1145/3230674
Govindu V(2016)Motion Averaging in 3D Reconstruction ProblemsRiemannian Computing in Computer Vision10.1007/978-3-319-22957-7_7(145-164)Online publication date: 2016
https://doi.org/10.1007/978-3-319-22957-7_7
Zhang LDong HSaddik A(2015)From 3D Sensing to PrintingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/281871012:2(1-23)Online publication date: 20-Oct-2015
https://dl.acm.org/doi/10.1145/2818710
Thöner MKuijper A(2015)Delta Global Illumination for Mixed RealityVirtual, Augmented and Mixed Reality10.1007/978-3-319-21067-4_13(108-118)Online publication date: 21-Jul-2015
https://doi.org/10.1007/978-3-319-21067-4_13
Transue SChoi M(2014)Intuitive Alignment of Point-Clouds with Painting-Based Feature CorrespondenceAdvances in Visual Computing10.1007/978-3-319-14364-4_72(746-756)Online publication date: 2014
https://doi.org/10.1007/978-3-319-14364-4_72

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