Special Issue "Innovative Sensing - From Sensors to Methods and Applications"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 3 February 2019

Special Issue Editors

Guest Editor
Professor Boris Jutzi

Adjunct Professor, Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Englerstr. 7, Karlsruhe, Germany
Website | E-Mail
Interests: Active Sensors, Computer Vision, Laserscanning, Optical Measurement Technology, Signal & Image Processing
Guest Editor
Dr. Martin Weinmann

Assistant Professor, Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Englerstr. 7, Karlsruhe, Germany
Website | E-Mail
Interests: Computer Vision, Pattern Recognition, Machine Learning, 3D Vision, Laser Scanning
Guest Editor
Prof. Dr. Raul Queiroz Feitosa

Pontifical Catholic University of Rio de Janeiro, Department of Electrical Engineering, rua Marquês de São Vicente, 225, Rio de Janeiro, RJ - Brazil - 22451-900
Website | E-Mail
Phone: +55 21 35271212
Fax: +55 21 35271232
Interests: image analysis, machine learning, remote sensing, biometrics
Guest Editor
Professor Stefan Hinz

Institute of Photogrammetry and Remote Sensing, Karlsruhe Institute of Technology (KIT), Englerstr. 7, Karlsruhe, Germany
Website | E-Mail
Interests: Image Analysis, Remote Sensing, Computer Vision, Digital Image Processing, Pattern Recognition, Machine Learning

Special Issue Information

Dear Colleagues,

 

Recent years have been characterized by rapid developments in various fields of sensor technology, design of smart sensor networks, unmanned platforms and new satellite imaging concepts or satellite constellations, respectively. This includes the sector of–often low-cost–industrial imaging sensors and, likewise, the development of highly sophisticated and specialized sensors for Earth Observation, thereby covering multiple modes of active or passive sensor technology and various scales of imaging.

 

With this Special Issue on "Innovative Sensing—From Sensors to Methods and Applications" we address research methods as well as applications on the design, construction, characterization, calibration and use of imaging and non-imaging sensors, sensor systems and sensor networks for photogrammetry, remote sensing and spatial information science. This includes the development of new and innovative technological concepts, likewise, models and methods to optimally exploit, calibrate and thoroughly evaluate new sensors, networks and single sensor components.

 

Prospective authors are cordially invited to contribute to this Special Issue by submitting an article containing original research.

 

Prof. Dr. Boris Jutzi
Dr. Martin Weinmann
Prof. Dr. Raul Feitosa
Prof. Dr. Stefan Hinz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

Open AccessArticle Deep Learning Segmentation and 3D Reconstruction of Road Markings Using Multiview Aerial Imagery
ISPRS Int. J. Geo-Inf. 2019, 8(1), 47; https://doi.org/10.3390/ijgi8010047
Received: 14 December 2018 / Revised: 15 January 2019 / Accepted: 16 January 2019 / Published: 18 January 2019
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Abstract
The 3D information of road infrastructures is growing in importance with the development of autonomous driving. In this context, the exact 2D position of road markings as well as height information play an important role in, e.g., lane-accurate self-localization of autonomous vehicles. In
[...] Read more.
The 3D information of road infrastructures is growing in importance with the development of autonomous driving. In this context, the exact 2D position of road markings as well as height information play an important role in, e.g., lane-accurate self-localization of autonomous vehicles. In this paper, the overall task is divided into an automatic segmentation followed by a refined 3D reconstruction. For the segmentation task, we applied a wavelet-enhanced fully convolutional network on multiview high-resolution aerial imagery. Based on the resulting 2D segments in the original images, we propose a successive workflow for the 3D reconstruction of road markings based on a least-squares line-fitting in multiview imagery. The 3D reconstruction exploits the line character of road markings with the aim to optimize the best 3D line location by minimizing the distance from its back projection to the detected 2D line in all the covering images. Results showed an improved IoU of the automatic road marking segmentation by exploiting the multiview character of the aerial images and a more accurate 3D reconstruction of the road surface compared to the semiglobal matching (SGM) algorithm. Further, the approach avoids the matching problem in non-textured image parts and is not limited to lines of finite length. In this paper, the approach is presented and validated on several aerial image data sets covering different scenarios like motorways and urban regions. Full article
(This article belongs to the Special Issue Innovative Sensing - From Sensors to Methods and Applications)
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