Visual Mapping in Light-Crowded Indoor Environments

Jan Helge Klüssendorff; Kristian Ehlers; Erik Maehle

doi:10.1007/978-3-319-08338-4_66

Visual Mapping in Light-Crowded Indoor Environments

Jan Helge Klüssendorff, Kristian Ehlers, Erik Maehle

Institute of Computer Engineering

Abstract

Due to the recent success of affordable RGBD cameras, solutionsKlüssendorff, Jan Helgeto the Visual Simultaneous Localization and Mapping (VSLAM) problem has experienced a huge leap. To enableEhlers, Kristianaccurate mappingMaehle, Eriksolutions, most of the proposed solutions expect static environments. Thinking of industrial applications, there is no guarantee for static environments. The SLAM algorithm has to cope with moving objects like human beings. We present an approach to detect moving objects in RGBD camera images. The approach is based on point cloud and image filtering techniques. We present test results using publicly available datasets. We further show the performance and influence of the algorithm on mapping and on the accuracy of a visual SLAM system.

Original language	English
Title of host publication	Intelligent Autonomous Systems 13
Editors	Emanuele Menegatti, Nathan Michael, Karsten Berns, Hiroaki Yamaguchi
Number of pages	10
Volume	302
Place of Publication	Cham
Publisher	Springer International Publishing
Publication date	03.09.2015
Pages	913-922
ISBN (Print)	978-3-319-08337-7
ISBN (Electronic)	978-3-319-08338-4
DOIs	https://doi.org/10.1007/978-3-319-08338-4_66
Publication status	Published - 03.09.2015
Event	13th International Conference on Intelligent Autonomous Systems - Padova, Italy Duration: 14.07.2014 → 18.07.2014 Conference number: 140839

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Cite this

@inproceedings{17c6ba1f241e4bddb8281a71339a5827,

title = "Visual Mapping in Light-Crowded Indoor Environments",

abstract = "Due to the recent success of affordable RGBD cameras, solutionsKl{\"u}ssendorff, Jan Helgeto the Visual Simultaneous Localization and Mapping (VSLAM) problem has experienced a huge leap. To enableEhlers, Kristianaccurate mappingMaehle, Eriksolutions, most of the proposed solutions expect static environments. Thinking of industrial applications, there is no guarantee for static environments. The SLAM algorithm has to cope with moving objects like human beings. We present an approach to detect moving objects in RGBD camera images. The approach is based on point cloud and image filtering techniques. We present test results using publicly available datasets. We further show the performance and influence of the algorithm on mapping and on the accuracy of a visual SLAM system.",

author = "Kl{\"u}ssendorff, {Jan Helge} and Kristian Ehlers and Erik Maehle",

year = "2015",

month = sep,

day = "3",

doi = "10.1007/978-3-319-08338-4_66",

language = "English",

isbn = "978-3-319-08337-7",

volume = "302",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer International Publishing",

pages = "913--922",

editor = "Emanuele Menegatti and Nathan Michael and Karsten Berns and Hiroaki Yamaguchi",

booktitle = "Intelligent Autonomous Systems 13",

note = "13th International Conference on Intelligent Autonomous Systems, IAS 2014 ; Conference date: 14-07-2014 Through 18-07-2014",

}

Klüssendorff, JH, Ehlers, K & Maehle, E 2015, Visual Mapping in Light-Crowded Indoor Environments. in E Menegatti, N Michael, K Berns & H Yamaguchi (eds), Intelligent Autonomous Systems 13. vol. 302, Advances in Intelligent Systems and Computing, vol. 302, Springer International Publishing, Cham, pp. 913-922, 13th International Conference on Intelligent Autonomous Systems, Padova, Italy, 14.07.14. https://doi.org/10.1007/978-3-319-08338-4_66

Visual Mapping in Light-Crowded Indoor Environments. / Klüssendorff, Jan Helge; Ehlers, Kristian; Maehle, Erik.
Intelligent Autonomous Systems 13. ed. / Emanuele Menegatti; Nathan Michael; Karsten Berns; Hiroaki Yamaguchi. Vol. 302 Cham: Springer International Publishing, 2015. p. 913-922 (Advances in Intelligent Systems and Computing; Vol. 302).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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AU - Ehlers, Kristian

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N2 - Due to the recent success of affordable RGBD cameras, solutionsKlüssendorff, Jan Helgeto the Visual Simultaneous Localization and Mapping (VSLAM) problem has experienced a huge leap. To enableEhlers, Kristianaccurate mappingMaehle, Eriksolutions, most of the proposed solutions expect static environments. Thinking of industrial applications, there is no guarantee for static environments. The SLAM algorithm has to cope with moving objects like human beings. We present an approach to detect moving objects in RGBD camera images. The approach is based on point cloud and image filtering techniques. We present test results using publicly available datasets. We further show the performance and influence of the algorithm on mapping and on the accuracy of a visual SLAM system.

AB - Due to the recent success of affordable RGBD cameras, solutionsKlüssendorff, Jan Helgeto the Visual Simultaneous Localization and Mapping (VSLAM) problem has experienced a huge leap. To enableEhlers, Kristianaccurate mappingMaehle, Eriksolutions, most of the proposed solutions expect static environments. Thinking of industrial applications, there is no guarantee for static environments. The SLAM algorithm has to cope with moving objects like human beings. We present an approach to detect moving objects in RGBD camera images. The approach is based on point cloud and image filtering techniques. We present test results using publicly available datasets. We further show the performance and influence of the algorithm on mapping and on the accuracy of a visual SLAM system.

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A2 - Menegatti, Emanuele

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T2 - 13th International Conference on Intelligent Autonomous Systems

Y2 - 14 July 2014 through 18 July 2014

ER -

Visual Mapping in Light-Crowded Indoor Environments

Abstract

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