Special Issue "Depth Sensors and 3D Vision"
Deadline for manuscript submissions: closed (20 December 2018)
Prof. Dr. Roberto Vezzani
AImageLab, Dipartimento di Ingegneria "Enzo Ferrari", University of Modena and Reggio Emilia, Modena, Italy
Website | E-Mail
Interests: computer vision; image processing; machine vision; pattern recognition; surveillance; people behavior understanding; human-computer interaction; depth sensors; 3D vision
The recent diffusion of inexpensive RGB-D sensors has encouraged the computer vision community to explore new solutions based on depth images. Depth information provides a significant contribution to solve or simplify several challenging tasks, such as shape analysis and classification, scene reconstruction, object segmentation, people detection, and body part recognition. The intrinsic metric information as well as the ability to handle texture and illumination variations of objects and scenes are only two of the advantages with respect to pure RGB images.
For example, hardware and software technologies included in the Microsoft Kinect framework allow an easy estimation of the 3D positions of skeleton joints, providing a new compact and expressive representation of the human body.
Although the Kinect failed as a gaming-first device, it has been a launch pad for the spread of depth sensors and, contextually, 3D vision. From a hardware perspective, several stereo, structured IR light, and ToF sensors have appeared on the market, and are studied by the scientific community. At the same time, computer vision and machine learning communities have proposed new solutions to process depth data, individually or fused with other information such as RGB images.
This Special Issue seeks innovative work to explore new hardware and software solutions for the generation and analysis of depth data, including representation models, machine learning approaches, datasets, and benchmarks.
The particular topics of interest include, but are not limited to:
- Depth acquisition techniques
- Depth data processing
- Analysis of depth data
- Fusion of depth data with other modalities
- From and to depth domain translation
- 3D scene reconstruction
- 3D shape modeling and retrieval
- 3D object recognition
- 3D biometrics
- 3D imaging for cultural heritage applications
- Point cloud modelling and processing
- Human action recognition on depth data
- Biomedical applications of depth data
- Other applications of depth data analysis
- Depth datasets and benchmarks
- Depth data visualization
Prof. Roberto Vezzani
Manuscript Submission Information
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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 1800 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.
- Depth sensors
- 3D vision
- Depth data generation
- Depth data analysis
- Depth datasets