NDLI: Robust single view room structure segmentation in Manhattan-like environments from stereo vision

Content Provider	IEEE Xplore Digital Library
Author	Olufs, S. Vincze, M.
Copyright Year	2011
Description	Author affiliation: Vienna University of Technology, Automation and Control Institute, Gusshausstrasse 25-29 / E376, A-1040, Austria (Olufs, S.; Vincze, M.)
Abstract	In this paper we propose a novel approach for the robust segmentation of room structure using Manhattan world assumption i.e. the frequently observed dominance of three mutually orthogonal vanishing directions in man-made environments. First, separate histograms are generated for the Cartesian major axis, i.e. X, Y and Z, on stereo data with an arbitrary roll, pitch and yaw rotation. Using the traditional Markov particle filters and minimal entropy as metric on the histograms, we are able to estimate the camera orientation with respect to orthogonal structure. Once the orientation is estimated we extract a hypotheses of the room structure by exploiting 2D histograms using mean shift clustering techniques as rough estimate for a pre-segmentation of voxels i.e. plane orientation and position. We apply superpixel over segmentation on the colour input to achieve a dense segmentation. The over segmentation and pre-segmented voxels are combined using graph-cuts for a not a-priori known number of final plane segments with a a-expansion graph cut variant proposed by Delong et al. with polynomial runtime. We show the robustness of our approach with respect to noise in real world data.
Starting Page	5315
Ending Page	5322
File Size	2160652
Page Count	8
File Format	PDF
ISBN	9781612843865
ISSN	10504729
e-ISBN	9781612843858
DOI	10.1109/ICRA.2011.5980359
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Stereo vision Cameras Entropy Robustness Ellipsoids Image edge detection
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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