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Laryngo- Rhino- Otologie May 2023Human facial expressions are unique in their ability to express our emotions and communicate them to others. The mimic expression of basic emotions is very similar...
Human facial expressions are unique in their ability to express our emotions and communicate them to others. The mimic expression of basic emotions is very similar across different cultures and has also many features in common with other mammals. This suggests a common genetic origin of the association between facial expressions and emotion. However, recent studies also show cultural influences and differences. The recognition of emotions from facial expressions, as well as the process of expressing one's emotions facially, occurs within an extremely complex cerebral network. Due to the complexity of the cerebral processing system, there are a variety of neurological and psychiatric disorders that can significantly disrupt the coupling of facial expressions and emotions. Wearing masks also limits our ability to convey and recognize emotions through facial expressions. Through facial expressions, however, not only "real" emotions can be expressed, but also acted ones. Thus, facial expressions open up the possibility of faking socially desired expressions and also of consciously faking emotions. However, these pretenses are mostly imperfect and can be accompanied by short-term facial movements that indicate the emotions that are actually present (microexpressions). These microexpressions are of very short duration and often barely perceptible by humans, but they are the ideal application area for computer-aided analysis. This automatic identification of microexpressions has not only received scientific attention in recent years, but its use is also being tested in security-related areas. This article summarizes the current state of knowledge of facial expressions and emotions.
Topics: Humans; Emotions; Face; Facial Expression; Time Factors
PubMed: 37130535
DOI: 10.1055/a-2003-5687 -
Current Opinion in Neurobiology Jun 2021What are emotions and how should we study them? These questions give rise to ongoing controversy amongst scientists in the fields of neuroscience, psychology and... (Review)
Review
What are emotions and how should we study them? These questions give rise to ongoing controversy amongst scientists in the fields of neuroscience, psychology and philosophy, and have resulted in different views on emotions [1-6]. In this review, we define emotions as functional states that bear essential roles in promoting survival and thus have emerged through evolution. Emotions trigger behavioral, somatic, hormonal, and neurochemical reactions, referred to as expressions of emotion. We discuss recent studies on emotion expression across species and highlight emerging common principles. We argue that detailed and multidimensional analyses of emotion expressions are key to develop biology-based definitions of emotions and to reveal their neuronal underpinnings.
Topics: Emotions; Facial Expression; Neurons; Neurosciences
PubMed: 33548631
DOI: 10.1016/j.conb.2021.01.003 -
Sensors (Basel, Switzerland) Feb 2022Automatic facial expression recognition is essential for many potential applications. Thus, having a clear overview on existing datasets that have been investigated... (Review)
Review
Automatic facial expression recognition is essential for many potential applications. Thus, having a clear overview on existing datasets that have been investigated within the framework of face expression recognition is of paramount importance in designing and evaluating effective solutions, notably for neural networks-based training. In this survey, we provide a review of more than eighty facial expression datasets, while taking into account both macro- and micro-expressions. The proposed study is mostly focused on spontaneous and in-the-wild datasets, given the common trend in the research is that of considering contexts where expressions are shown in a spontaneous way and in a real context. We have also provided instances of potential applications of the investigated datasets, while putting into evidence their pros and cons. The proposed survey can help researchers to have a better understanding of the characteristics of the existing datasets, thus facilitating the choice of the data that best suits the particular context of their application.
Topics: Face; Facial Expression; Facial Recognition; Neural Networks, Computer
PubMed: 35214430
DOI: 10.3390/s22041524 -
Sensors (Basel, Switzerland) Jan 2021Understanding animal emotions is a key to unlocking methods for improving animal welfare. Currently there are no 'benchmarks' or any scientific assessments available for... (Review)
Review
Understanding animal emotions is a key to unlocking methods for improving animal welfare. Currently there are no 'benchmarks' or any scientific assessments available for measuring and quantifying the emotional responses of farm animals. Using sensors to collect biometric data as a means of measuring animal emotions is a topic of growing interest in agricultural technology. Here we reviewed several aspects of the use of sensor-based approaches in monitoring animal emotions, beginning with an introduction on animal emotions. Then we reviewed some of the available technological systems for analyzing animal emotions. These systems include a variety of sensors, the algorithms used to process biometric data taken from these sensors, facial expression, and sound analysis. We conclude that a single emotional expression measurement based on either the facial feature of animals or the physiological functions cannot show accurately the farm animal's emotional changes, and hence compound expression recognition measurement is required. We propose some novel ways to combine sensor technologies through sensor fusion into efficient systems for monitoring and measuring the animals' compound expression of emotions. Finally, we explore future perspectives in the field, including challenges and opportunities.
Topics: Animal Husbandry; Animal Welfare; Animals; Animals, Domestic; Emotions; Facial Expression; Livestock
PubMed: 33466737
DOI: 10.3390/s21020553 -
Dialogues in Clinical Neuroscience Dec 2015Research into emotions has increased in recent decades, especially on the subject of recognition of emotions. However, studies of the facial expressions of emotion were... (Review)
Review
Research into emotions has increased in recent decades, especially on the subject of recognition of emotions. However, studies of the facial expressions of emotion were compromised by technical problems with visible video analysis and electromyography in experimental settings. These have only recently been overcome. There have been new developments in the field of automated computerized facial recognition; allowing real-time identification of facial expression in social environments. This review addresses three approaches to measuring facial expression of emotion and describes their specific contributions to understanding emotion in the healthy population and in persons with mental illness. Despite recent progress, studies on human emotions have been hindered by the lack of consensus on an emotion theory suited to examining the dynamic aspects of emotion and its expression. Studying expression of emotion in patients with mental health conditions for diagnostic and therapeutic purposes will profit from theoretical and methodological progress.
Topics: Animals; Behavior; Electromyography; Emotions; Facial Expression; Humans; Neuropsychological Tests; Recognition, Psychology
PubMed: 26869846
DOI: 10.31887/DCNS.2015.17.4/kwolf -
Computational Intelligence and... 2021Emotion plays an important role in communication. For human-computer interaction, facial expression recognition has become an indispensable part. Recently, deep neural...
Emotion plays an important role in communication. For human-computer interaction, facial expression recognition has become an indispensable part. Recently, deep neural networks (DNNs) are widely used in this field and they overcome the limitations of conventional approaches. However, application of DNNs is very limited due to excessive hardware specifications requirement. Considering low hardware specifications used in real-life conditions, to gain better results without DNNs, in this paper, we propose an algorithm with the combination of the oriented FAST and rotated BRIEF (ORB) features and Local Binary Patterns (LBP) features extracted from facial expression. First of all, every image is passed through face detection algorithm to extract more effective features. Second, in order to increase computational speed, the ORB and LBP features are extracted from the face region; specifically, region division is innovatively employed in the traditional ORB to avoid the concentration of the features. The features are invariant to scale and grayscale as well as rotation changes. Finally, the combined features are classified by Support Vector Machine (SVM). The proposed method is evaluated on several challenging databases such as Cohn-Kanade database (CK+), Japanese Female Facial Expressions database (JAFFE), and MMI database; experimental results of seven emotion state (neutral, joy, sadness, surprise, anger, fear, and disgust) show that the proposed framework is effective and accurate.
Topics: Algorithms; Emotions; Face; Facial Expression; Facial Recognition; Female; Humans; Neural Networks, Computer
PubMed: 33505453
DOI: 10.1155/2021/8828245 -
Perception Feb 2023The judgment of female body appearance has been reported to be affected by a range of internal (e.g., viewers' sexual cognition) and external factors (e.g., viewed...
The judgment of female body appearance has been reported to be affected by a range of internal (e.g., viewers' sexual cognition) and external factors (e.g., viewed clothing type and colour). This eye-tracking study aimed to complement previous research by examining the effect of facial expression on female body perception and associated body-viewing gaze behaviour. We presented female body images of Caucasian avatars in a continuum of common dress sizes posing seven basic facial expressions (neutral, happiness, sadness, anger, fear, surprise, and disgust), and asked both male and female participants to rate the perceived body attractiveness and body size. The analysis revealed an evident modulatory role of avatar facial expressions on body attractiveness and body size ratings, but not on the amount of viewing time directed at individual body features. Specifically, happy and angry avatars attracted the highest and lowest body attractiveness ratings, respectively, and fearful and surprised avatars tended to be rated slimmer. Interestingly, the impact of facial expression on female body assessment was not further influenced by viewers' gender, suggesting a 'universal' role of common facial expressions in modifying the perception of female body appearance.
Topics: Humans; Male; Female; Facial Expression; Fear; Anger; Happiness; Body Image; Emotions
PubMed: 36415086
DOI: 10.1177/03010066221140254 -
Perception Apr 2021We often show an invariant or comparable recognition performance for perceiving prototypical facial expressions, such as happiness and anger, under different viewing...
We often show an invariant or comparable recognition performance for perceiving prototypical facial expressions, such as happiness and anger, under different viewing settings. However, it is unclear to what extent the categorisation of ambiguous expressions and associated interpretation bias are invariant in degraded viewing conditions. In this exploratory eye-tracking study, we systematically manipulated both facial expression ambiguity (via morphing happy and angry expressions in different proportions) and face image clarity/quality (via manipulating image resolution) to measure participants' expression categorisation performance, perceived expression intensity, and associated face-viewing gaze distribution. Our analysis revealed that increasing facial expression ambiguity and decreasing face image quality induced the opposite direction of expression interpretation bias (negativity vs. positivity bias, or increased anger vs. increased happiness categorisation), the same direction of deterioration impact on rating expression intensity, and qualitatively different influence on face-viewing gaze allocation (decreased gaze at eyes but increased gaze at mouth vs. stronger central fixation bias). These novel findings suggest that in comparison with prototypical facial expressions, our visual system has less perceptual tolerance in processing ambiguous expressions which are subject to viewing condition-dependent interpretation bias.
Topics: Anger; Emotions; Face; Facial Expression; Happiness; Humans; Recognition, Psychology
PubMed: 33709837
DOI: 10.1177/03010066211000270 -
Sensors (Basel, Switzerland) May 2022Automatic identification of human facial expressions has many potential applications in today's connected world, from mental health monitoring to feedback for onscreen...
Automatic identification of human facial expressions has many potential applications in today's connected world, from mental health monitoring to feedback for onscreen content or shop windows and sign-language prosodic identification. In this work we use visual information as input, namely, a dataset of face points delivered by a Kinect device. The most recent work on facial expression recognition uses Machine Learning techniques, to use a modular data-driven path of development instead of using human-invented ad hoc rules. In this paper, we present a Machine-Learning based method for automatic facial expression recognition that leverages information fusion architecture techniques from our previous work and soft voting. Our approach shows an average prediction performance clearly above the best state-of-the-art results for the dataset considered. These results provide further evidence of the usefulness of information fusion architectures rather than adopting the default ML approach of features aggregation.
Topics: Face; Facial Expression; Facial Recognition; Humans; Machine Learning; Politics
PubMed: 35684825
DOI: 10.3390/s22114206 -
Fa Yi Xue Za Zhi Oct 2023Research on facial micro-expression analysis has been going on for decades. Micro-expression can reflect the true emotions of individuals, and it has important... (Review)
Review
Research on facial micro-expression analysis has been going on for decades. Micro-expression can reflect the true emotions of individuals, and it has important application value in assisting auxiliary diagnosis and disease monitoring of mental disorders. In recent years, the development of artificial intelligence and big data technology has made the automatic recognition of micro-expressions possible, which will make micro-expression analysis more convenient and more widely used. This paper reviews the development of facial micro-expression analysis and its application in forensic psychiatry, to look into further application prospects and development direction.
Topics: Humans; Forensic Psychiatry; Artificial Intelligence; Mental Disorders; Facial Expression; Emotions
PubMed: 38006270
DOI: 10.12116/j.issn.1004-5619.2022.120104