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Scene Flow Estimation from Light Fields via the Preconditioned Primal-Dual Algorithm Read chapter Read first chapter

2014 | OriginalPaper | Chapter

Automatic 3D Reconstruction of Indoor Manhattan World Scenes Using Kinect Depth Data

Author : Dominik Wolters

Published in: Pattern Recognition

Publisher: Springer International Publishing

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Abstract

This paper discusses a system to reconstruct indoor scenes automatically and evaluates its accuracy and applicability. The focus is on the realization of a simple, quick and inexpensive way to map empty or slightly furnished rooms. The data is acquired with a Kinect sensor mounted onto a pan-tilt head. The Manhattan world assumption is used to approximate the environment. The approach for determining the wall, floor and ceiling planes of the rooms is based on a plane sweep method. The floor plan is reconstructed from the detected planes using an iterative flood fill algorithm. Furthermore, the developed method allows to detect doors and windows, generate 3D models of the measured rooms and to merge multiple scans.

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Metadata
Title
Automatic 3D Reconstruction of Indoor Manhattan World Scenes Using Kinect Depth Data
Author
Dominik Wolters
Copyright Year
2014
Book
Pattern Recognition

Print ISBN: 978-3-319-11751-5

Electronic ISBN: 978-3-319-11752-2

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-11752-2_59

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