Advances in Emotional Body Gesture Recognition

Dear Colleagues,

Recognition of emotional states in the context of affective computing is a longstanding goal of many researchers. Most studies have focused on facial expressions or speech, and recently a combination of both. In many papers, the authors indicate the necessity of fusing a variety of information, which  is integral to the human cognitive process.

The development of motion capture technologies such as structured-light 3D scanners, time-of-flight sensors, and more recently, Densepose mapping, has caused a surge of interest regarding the influence of gestures on emotional resonance. Gestures, as one of the most important forms of nonverbal communication, allow individuals to communicate a variety of feelings, thoughts, and emotions. However due to the limited amount of publicly accessible databases with emotional gestures as an additional mode, trimodality based recognition is still a challenging task, and there is clearly a gap to be filled regarding this kind of analysis.

This Special Issue invites contributions that address (i) systems and devices for capturing emotions based on gestures, and (ii) machine-learning techniques of relevance for tackling the issues above. In particular, submitted papers should clearly show novel contributions and innovative applications covering, but not limited to, the following topics around emotion recognition:

• Systems and devices for capturing gestures;
• Affective database creation, experimental datasets;
• Data preprocessing;
• Nonintrusive sensor technologies;
• Emotion recognition using mobile phones and smart bracelets;
• Machine-learning techniques for emotion recognition;   
• Deep learning for emotion recognition.

Prof. Dr. Gholamreza Anbarjafari
Dr. Dorota Kamińska
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. Applied Sciences 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.

• systems and devices for capturing gestures
• affective database creation, experimental datasets
• data preprocessing
• nonintrusive sensor technologies
• emotion recognition using mobile phones and smart bracelets
• machine-learning techniques for emotion recognition
• deep learning for emotion recognition