Vision- and Sensor-Based Sensing in Human Activity Recognition—Second Edition
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: 10 May 2026 | Viewed by 1489
Special Issue Editors
Interests: pattern recognition; character recognition; image processing; computer vision; human–computer interaction; neurological disease analysis; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: volumetric holographic optical element (VHOE)-based augmented reality (AR) devices, such as transparent projection display, HUD and holo glasses and integral imaging display, hologram image processing
Special Issue Information
Dear Colleagues,
Following the success of the previous Special Issue "Vision- and Sensor-Based Sensing in Human Activity Recognition" (https://www.mdpi.com/journal/sensors/special_issues/Human_Activity), we are pleased to announce the next in the series, entitled "Vision- and Sensor-Based Sensing in Human Activity Recognition—Second Edition".
The goal of this Special Issue is to help to overcome the gap between human activity recognition and its involvement in the development of many important applications, including human–computer interaction (HCI), virtual reality, security, the internet of things (IoT), and healthcare facilities.
Over the past few decades, video- or sensor-based sensing for human activity recognition has received tremendous attention from the research community due to its wide range of applications and the recent advancement of computational performance, camera and sensor technology, and algorithms of machine learning and deep learning.
In this Special Issue on vision- and sensor-based sensing in human activity recognition, we are aiming to publish novel and technically sound research articles that demonstrate theoretical and practical contributions to computer vision, machine learning, AI, sensing, and medical and social issues.
Topics of interest include, but are not limited to, the following:
Human activity recognition from camera, video, and other relevant sensor data
Non-touch and touch interfaces using human activity
Deep learning approach for human activity recognition
Handwriting activity analysis and recognition
Medical diagnosis and recognition using human activity
Biosignal processing for human activity recognition
Healthcare application using human activity
Virtual reality, augmented reality, and other applications using human activity
Human activity analysis and recognition for social issues
Large datasets on human activity recognition
Current state-of-the-art and future trends of human activity recognition
Prof. Dr. Jungpil Shin
Dr. Young-Suk Hwang
Guest Editors
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Keywords
- behavior modeling
- activity recognition
- deep learning
- explainable AI
- context understanding
- causality knowledge
- activity representation
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Related Special Issue
- Vision and Sensor-Based Sensing in Human Action Recognition in Sensors (15 articles)
