Special Issue "Emotions Detection through Facial Recognitions"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: closed (10 November 2021).

Special Issue Editor

Dr. Amir Dirin
E-Mail Website
Guest Editor
Edcuational Technology at Helsinki University; Haaga-helia University of Applied Science
Interests: User Experience; Immersive AR/VR; Emotional Detection; Facial Reconginition Algorithm

Special Issue Information

Dear Colleagues,

The popularity of smart gadgets and the advancement of camera capabilities have resulted in the concept of facial recognition becoming a hot topic among academicics and practitioners. Facial recognition is a way of recognizing a human face with the help of a computer vision algorithm. Traditionally, facial recognition algorithms are mainly employed in the surveillance system but nowadays have been expanded to other fields including entertainment, e.g., Snapchat.

Emotion detection has been the most challenging and yet interesting research topic in recent years. Emotional expressions are rooted in many psychological and physiological factors; therefore, reliable and accurate detection of emotions through facial expressions is not an easy task.

Therefore, the aim of this Special Issue is to present and publish the latest developments in emotion detection based on facial recognition algorithms and related experiments. Researchers in both communities are invited to share their original, unpublished works through this Special Issues.

Topics of interest include, but are not limited to:

  • Emotion detection algorithm design and evaluation;
  • Case studies of emotional detection;
  • Emotional detection experiments based on the commercial products;
  • Applications’ concept of emotion detection through facial recognitions;
  • Security and privacy concern in emotional detection;
  • Social media and emotional detection based on facial recognition.

Dr. Amir Dirin
Guest Editor

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. Information is an international peer-reviewed open access monthly 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 1400 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.


  • Emotion detections
  • Facial Recognitions Algorithm
  • Applications of emotional detection
  • Security and Privacy

Published Papers (1 paper)

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The Effects of Facial Expressions on Face Biometric System’s Reliability
Information 2020, 11(10), 485; https://doi.org/10.3390/info11100485 - 17 Oct 2020
Viewed by 1225
The human mood has a temporary effect on the face shape due to the movement of its muscles. Happiness, sadness, fear, anger, and other emotional conditions may affect the face biometric system’s reliability. Most of the current studies on facial expressions are concerned [...] Read more.
The human mood has a temporary effect on the face shape due to the movement of its muscles. Happiness, sadness, fear, anger, and other emotional conditions may affect the face biometric system’s reliability. Most of the current studies on facial expressions are concerned about the accuracy of classifying the subjects based on their expressions. This study investigated the effect of facial expressions on the reliability of a face biometric system to find out which facial expression puts the biometric system at greater risk. Moreover, it identified a set of facial features that have the lowest facial deformation caused by facial expressions to be generalized during the recognition process, regardless of which facial expression is presented. In order to achieve the goal of this study, an analysis of 22 facial features between the normal face and six universal facial expressions is obtained. The results show that the face biometric systems are affected by facial expressions where the disgust expression achieved the most dissimilar score, while the sad expression achieved the lowest dissimilar score. Additionally, the study identified the five and top ten facial features that have the lowest facial deformations on the face shape in all facial expressions. Besides that, the relativity score showed less variances between the sample using the top facial features. The obtained results of this study minimized the false rejection rate in the face biometric system and subsequently the ability to raise the system’s acceptance threshold to maximize the intrusion detection rate without affecting the user convenience. Full article
(This article belongs to the Special Issue Emotions Detection through Facial Recognitions)
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