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Feature Papers in Sensing and Imaging 2025

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 486

Special Issue Editors


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Guest Editor
Laboratoire Hubert Curien, CNRS UMR 5516, Université de Lyon, 42000 Saint-Étienne, France
Interests: fiber sensors; optical sensors; image sensors; optical materials; radiation effects
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Department of Computer Science, University of Applied Sciences and Arts Dortmund (FH Dortmund), 44227 Dortmund, Germany
2. Institute for Medical Informatics, Biometry and Epidemiology (IMIBE), University Hospital Essen, 45122 Essen, Germany
Interests: machine learning; computational intelligence; biomedical applications; interpretable machine learning; natural language processing (NLP); computer vision; augmented reality; information extraction; information retrieval; image processing; biostatistics; bioinformatics; mathematics for computer science
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland
Interests: image denoising; image segmentation; image super-resolution; object detection; deep learning-based filtering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce that the Sensors Section ‘Sensing and Imaging’ is now compiling a collection of papers submitted by the Editorial Board Members (EBMs) of our section and outstanding scholars in this research field. We welcome contributions and recommendations from the EBMs.

We are seeking original papers and review articles that showcase state-of-the-art theoretical and applicative advances, new experimental discoveries, and novel technological improvements regarding sensing and imaging. We expect these papers to be widely read and highly influential within the field. All papers in this Special Issue will be well promoted.

We would also like to take this opportunity to call on more experienced scholars to join the Section ‘Sensing and Imaging’ so that we can work together to further develop this exciting field of research.

Prof. Dr. Sylvain Girard
Prof. Dr. Christoph M. Friedrich
Prof. Dr. Bogdan Smolka
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 submissions that pass pre-check are 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 2600 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.

Keywords

  • imaging systems
  • sensors
  • camera
  • radar and sonar
  • probes
  • diagnostics (bio)medical imaging
  • subsurface and surface sensing
  • environmental sensing and imaging
  • nondestructive sensing and imaging
  • aerial/UAV imaging
  • gesture/pattern/target recognition
  • computer vision
  • imaging in harsh environments
  • extended reality (mixed/augmented/virtual reality)
  • material appearance metrology
  • acoustic/ultrasound/photoacoustic imaging
  • optical/infrared/spectral/hyperspectral/fluorescence imaging
  • (micro)wave/terahertz imaging
  • thermal imaging
  • magnetic imaging/atomic scale magnetic sensing and imaging
  • (high dynamic) range imaging 
  • 2D/3D imaging
  • computational imaging
  • unconventional imaging
  • artificial intelligence (AI)
  • machine/deep learning
  • (convolutional) neutral network

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Published Papers (1 paper)

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Research

42 pages, 47882 KiB  
Article
Product Engagement Detection Using Multi-Camera 3D Skeleton Reconstruction and Gaze Estimation
by Matus Tanonwong, Yu Zhu, Naoya Chiba and Koichi Hashimoto
Sensors 2025, 25(10), 3031; https://doi.org/10.3390/s25103031 - 11 May 2025
Viewed by 271
Abstract
Product engagement detection in retail environments is critical for understanding customer preferences through nonverbal cues such as gaze and hand movements. This study presents a system leveraging a 360-degree top-view fisheye camera combined with two perspective cameras, the only sensors required for deployment, [...] Read more.
Product engagement detection in retail environments is critical for understanding customer preferences through nonverbal cues such as gaze and hand movements. This study presents a system leveraging a 360-degree top-view fisheye camera combined with two perspective cameras, the only sensors required for deployment, effectively capturing subtle interactions even under occlusion or distant camera setups. Unlike conventional image-based gaze estimation methods that are sensitive to background variations and require capturing a person’s full appearance, raising privacy concerns, our approach utilizes a novel Transformer-based encoder operating directly on 3D skeletal keypoints. This innovation significantly reduces privacy risks by avoiding personal appearance data and benefits from ongoing advancements in accurate skeleton estimation techniques. Experimental evaluation in a simulated retail environment demonstrates that our method effectively identifies critical gaze-object and hand-object interactions, reliably detecting customer engagement prior to product selection. Despite yielding slightly higher mean angular errors in gaze estimation compared to a recent image-based method, the Transformer-based model achieves comparable performance in gaze-object detection. Its robustness, generalizability, and inherent privacy preservation make it particularly suitable for deployment in practical retail scenarios such as convenience stores, supermarkets, and shopping malls, highlighting its superiority in real-world applicability. Full article
(This article belongs to the Special Issue Feature Papers in Sensing and Imaging 2025)
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