loading
Papers Papers/2020

Research.Publish.Connect.

Paper

Authors: Julian Seuffert ; Ana Grassi ; Tobias Scheck and Gangolf Hirtz

Affiliation: Faculty of Electrical Engineering and Information Technology, Chemnitz University of Technology, Reichenhainer Str. 70, Chemnitz, Germany

ISBN: 978-989-758-488-6

Keyword(s): Omnidirectional, Fish Eye, Indoor, 3D, CNN, Stereo Vision.

Abstract: Stereo vision is one of the most prominent strategies to reconstruct a 3D scene with computer vision techniques. With the advent of Convolutional Neural Networks (CNN), stereo vision has undergone a breakthrough. Always more works attend to recover the depth information from stereo images by using CNNs. However, most of the existing approaches are developed for images captured with perspective cameras. Perspective cameras have a very limited field of view of around 60◦ and only a small portion of a scene can be reconstructed with a standard binocular stereo system. In the last decades, much effort has been conducted in the research field of omnidirectional stereo vision, which allows an almost complete scene reconstruction if the cameras are mounted at the ceiling. However, as omnidirectional images show strong distortion artifacts, most of the approaches perform an image warping to reduce the reconstruction complexity. In this work, we examine the impact of the omnidirectional image distortion on the learning process of a CNN. We compare the results of a network training with perspective and omnidirectional stereo images. For this work, we use AnyNet and a novel dataset of synthetic omnidirectional and perspective stereo images. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.192.27.11

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Seuffert, J.; Grassi, A.; Scheck, T. and Hirtz, G. (2021). A Study on the Influence of Omnidirectional Distortion on CNN-based Stereo Vision.In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-488-6, pages 809-816. DOI: 10.5220/0010324808090816

@conference{visapp21,
author={Julian Seuffert. and Ana Grassi. and Tobias Scheck. and Gangolf Hirtz.},
title={A Study on the Influence of Omnidirectional Distortion on CNN-based Stereo Vision},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2021},
pages={809-816},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010324808090816},
isbn={978-989-758-488-6},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - A Study on the Influence of Omnidirectional Distortion on CNN-based Stereo Vision
SN - 978-989-758-488-6
AU - Seuffert, J.
AU - Grassi, A.
AU - Scheck, T.
AU - Hirtz, G.
PY - 2021
SP - 809
EP - 816
DO - 10.5220/0010324808090816

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.