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Special Issue "Intelligent Sensors for Human Motion Analysis"

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

Deadline for manuscript submissions: 30 September 2021.

Special Issue Editors

Dr. Tomasz Krzeszowski
Website
Guest Editor
Faculty of Electrical and Computer Engineering, Rzeszow University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszow, Poland
Interests: human motion tracking; human body pose estimation; particle swarm optimization; parallel and distributed computing; gait recognition
Dr. Adam Świtoński
Website
Guest Editor
Department of Graphics, Computer Vision and Digital Systems, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland
Interests: processing and classification of motion capture data; time series analysis; machine learning; computer vision
Dr. Michal Kepski
Website
Guest Editor
Institute of Computer Science, University of Rzeszow, 1 Pigonia Str., 35-310 Rzeszow, Poland
Interests: fall detection; human motion tracking; action recognition
Prof. Dr. Carlos Tavares Calafate
Website
Guest Editor
Department of Computer Engineering, Technical University of Valencia, Valencia, Spain
Interests: ad-hoc and vehicular networks; UAVs, smart cities and IoT; QoS; network protocols; video streaming; network security
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Current visual analysis of human motion is one of the most interesting and active research topics in computer vision. This great interest is due to the wide spectrum of promising applications in many areas such as surveillance systems, medicine, athletic performance analysis, human–computer interaction, virtual reality, etc. Human motion analysis concerns the detection, tracking, and recognition of people and their activities based on data recorded by various types of sensors. In these studies, RGB and depth cameras are used. Moreover, studies aimed at developing methods for gait and action recognition often use motion capture systems based on active or passive markers as well as IMU sensors. These systems are very challenging to develop and, at the same time, have great promise for addressing research problems, especially if only visual data are used. Therefore, we welcome the submission of high-quality publications from researchers working on human pose estimation and tracking in addition to related topics such as activity recognition, gait recognition, and human–computer interaction, to name but a few examples. More precisely, the relevant topics for this Special Issue include (but are not limited to):

  • Human pose estimation
  • Articulated pose tracking
  • Multi-person 3D pose estimation
  • Action recognition
  • Gait recognition
  • Gesture recognition
  • Human fall detection
  • Pose/shape modeling and rendering
  • Future 3D pose prediction
  • Human–computer interaction
  • Synthetic data and data annotation for 3D human pose
  • Application of human motion analysis methods (e.g., robotics, surveillance, medicine).

Dr. Tomasz Krzeszowski
Dr. Adam Świtoński
Dr. Michal Kepski
Prof. Dr. Carlos Tavares Calafate
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. 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 2200 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

  • human pose estimation
  • articulated pose tracking
  • human motion tracking
  • action recognition
  • gait recognition
  • gesture recognition
  • human fall detection
  • human–computer interaction
  • markerless motion capture
  • marker-based motion capture

Published Papers (1 paper)

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Research

Open AccessArticle
Combined Regularized Discriminant Analysis and Swarm Intelligence Techniques for Gait Recognition
Sensors 2020, 20(23), 6794; https://doi.org/10.3390/s20236794 - 27 Nov 2020
Abstract
In the gait recognition problem, most studies are devoted to developing gait descriptors rather than introducing new classification methods. This paper proposes hybrid methods that combine regularized discriminant analysis (RDA) and swarm intelligence techniques for gait recognition. The purpose of this study is [...] Read more.
In the gait recognition problem, most studies are devoted to developing gait descriptors rather than introducing new classification methods. This paper proposes hybrid methods that combine regularized discriminant analysis (RDA) and swarm intelligence techniques for gait recognition. The purpose of this study is to develop strategies that will achieve better gait recognition results than those achieved by classical classification methods. In our approach, particle swarm optimization (PSO), grey wolf optimization (GWO), and whale optimization algorithm (WOA) are used. These techniques tune the observation weights and hyperparameters of the RDA method to minimize the objective function. The experiments conducted on the GPJATK dataset proved the validity of the proposed concept. Full article
(This article belongs to the Special Issue Intelligent Sensors for Human Motion Analysis)
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