Special Issue "Computer Vision for 3D Perception and Applications"
Deadline for manuscript submissions: 31 December 2020.
Interests: computer vision; deep learning; depth perception; embedded systems
Interests: computer vision; image processing; machine vision; pattern recognition; visual analysis of peoples' whereabouts; surveillance; traffic monitoring
Special Issues and Collections in MDPI journals
Effective 3D perception of the environment greatly enriches the knowledge of the surrounding environment and is crucial to effectively develop high-level applications for various purposes. Pivotal to 3D perception is the acquisition/estimation of reliable depth information—a task for which several technologies exist, ranging from active sensors (e.g., Time-of-Flight devices) to passive cameras, coupled with a variety of different techniques allowing for depth estimation from images (stereo matching, structure from motion, and more). From an accurate reconstruction of the surrounding 3D scene, several complex problems can be addressed, such as autonomous navigation and localization, tracking, surveillance, robotics, interaction with other agents, and manipulation of the sensed environment. In this field as well, the recent advances in deep learning have rapidly found place and spread.
The aim of this Special Issue is to present both techniques to reliably acquire 3D data and to tackle computer vision tasks by exploiting this information, exploring novel solutions for perception, as well as for applications.
This Special Issue invites contributions in the following topics (but is not limited to these):
- Depth from images;
- Binocular and multi-view stereo;
- Active depth sensing;
- Single image depth estimation;
- 3D reconstruction scene understanding;
- RGB-D computer vision;
- 3D pose estimation, tracking and recognition;
- 3D motion estimation;
- 3D semantic segmentation;
- Applications of 3D vision (e.g., robotics, augmented reality).
Dr. Matteo Poggi
Prof. Dr. Thomas Moeslund
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. Sensors is an international peer-reviewed open access semimonthly 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 2000 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.
- 3D perception
- binocular-multiview stereo
- active 3D sensors
- RGB-D computer vision
- 3D detection
- 3D tracking
- 3D vision applications
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
RGB-D data and algorithms for vision-based Human Robot Interaction (A. D'Eusanio, S. Pini, G. Borghi, R. Vezzani and R. Cucchiara)
Deep Learning for transient image reconstruction from ToF data ( Gianluca Agresti, Adriano Simonetto, Enrico Buratto, Hernik Schaefer and Pietro Zanuttigh)
3D Perception (Mikael Persson and Michael Felsberg)
3D reconstruction of sewer pipes using Time-of-flight and structured light sensors (Chris Holmberg Bahnsen, Anders Skaarup Johansen, Jesper Wædeled Henriksen and Thomas B. Moeslund)
Robust stereo matching on embedded systems (Filippo Aleotti, Fabio Tosi, Matteo Poggi and Stefano Mattoccia)