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Authors: M. A. A. Rajput 1 ; E. Funk 1 ; A. Börner 1 and O. Hellwich 2

Affiliations: 1 German Aerospace Center, Germany ; 2 Technical University Berlin, Germany

Keyword(s): Large Scale Automated 3D Modelling, Mobile Robotics, Efficient Data Structures, 3D Database.

Related Ontology Subjects/Areas/Topics: 3D Virtual Environments and Surveillance Applications ; Image and Video Processing, Compression and Segmentation ; Multimedia ; Multimedia Signal Processing ; Multimedia Systems and Applications ; Telecommunications

Abstract: 3D reconstruction from mobile image sensors is crucial for many offline-inspection and online robotic application. While several techniques are known today to deliver high accuracy 3D models from images via offline-processing, 3D reconstruction in real-time remains a major goal still to achieve. This work focuses on incremental 3D modeling from error prone depth image data, since standard 3D fusion techniques are tailored on accurate depth data from active sensors such as the Kinect. Imprecise depth data is usually provided by stereo camera sensors or simultaneous localization and mapping (SLAM) techniques. This work proposes an incremental extension of the total variation (TV) filtering technique, which is shown to reduce the errors of the reconstructed 3D model by up to 77% compared to state of the art techniques.

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Paper citation in several formats:
Rajput, M.; Funk, E.; Börner, A. and Hellwich, O. (2016). Recursive Total Variation Filtering Based 3D Fusion. In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - SIGMAP; ISBN 978-989-758-196-0; ISSN 2184-3236, SciTePress, pages 72-80. DOI: 10.5220/0005967700720080

@conference{sigmap16,
author={M. A. A. Rajput. and E. Funk. and A. Börner. and O. Hellwich.},
title={Recursive Total Variation Filtering Based 3D Fusion},
booktitle={Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - SIGMAP},
year={2016},
pages={72-80},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005967700720080},
isbn={978-989-758-196-0},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - SIGMAP
TI - Recursive Total Variation Filtering Based 3D Fusion
SN - 978-989-758-196-0
IS - 2184-3236
AU - Rajput, M.
AU - Funk, E.
AU - Börner, A.
AU - Hellwich, O.
PY - 2016
SP - 72
EP - 80
DO - 10.5220/0005967700720080
PB - SciTePress