Special Issue "Sensors-Based Human Action and Emotion Recognition"
Deadline for manuscript submissions: 15 November 2022 | Viewed by 4906
Interests: fire and smoke detection; advanced driver assistant system; human detection and tracking; analysis of remote sensing images; human action recognition; medical image processing
Special Issues, Collections and Topics in MDPI journals
Special Issue in Sensors: Intelligent Sensor Signal in Machine Learning
Special Issue in Sensors: Natural Disaster Prediction Based on Intelligent Sensor and Machine Learning
Special Issue in Sensors: Intelligent Sensor Signal in Machine Learning II
Human action and emotion recognition (HAER) technology, which analyzes data collected from various types of sensing devices including vision and embedded sensors, can be used in virtual reality (VR), argumented reality (VR), video surveillance, sport analysis, human–computer interaction, and healthcare. It has been applied to the development of various context-aware applications in emerging application areas.
In particular, recently, HAER research using deep learning technology instead of traditional machine learning has been actively conducted. A large-scale, well-annotated HAER-related database is required for HAER with high accuracy. Recently, the popularity of research on sensor (video)-based HAER is increasing, using the publicly available HAER-related database.
The purpose of this Special Issue is to take this opportunity to introduce the current developments of sensor- and video-based human action and emotion recognition combined with machine learning, including computer vision, pattern recognition, expert systems, deep learning, and so on. In this Special Issue, you are invited to submit contributions of original research, advancement, developments, and experiments pertaining to machine learning combined with sensors. Therefore, this Special Issue welcomes newly developed methods and ideas combining data obtained from various sensors in the following fields (but not limited to these fields):
- HAER based on machine learning;
- Deep network structure/learning algorithm for HAER;
- HAER based on sensor fusion techniques based on machine learning;
- Face and gaze recognition for HAER;
- Multi-modal/task learning for HAER decision-making and control;
- HAER technologies in autonomous vehicles;
- State of practice, research overview, experience reports, industrial experiments, and case studies in HAER.
Prof. Dr. ByoungChul Ko
Prof. Dr. Jong-Ha Lee
If you want to learn more information or need any advice, you can contact the Special Issue Editor Bell Ding via <[email protected]>
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 2400 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.