A forest experience does not always evoke positive emotion: A pilot study on unconscious facial expressions using the face reading technology

We report three studies exploring the relationship between disgust and trust. Study 1a measured emotions using face-reading technology while participants played a repeated trust game. We observed a negative correlation between trust and disgust. Study 1b employed self-reports along with the face reader. The self-report procedure adversely affected participants’ emotional state and eliminated the correlation between trust and other emotions. Study 2 induced incidental disgust or sadness using virtual reality and manipulated participants’ awareness of the source of their emotions. Disgusted participants judged others as less trustworthy and sent less in a trust game than sad or control participants. An interaction indicated that awareness of the source of emotions eliminated the effect. Our data are consistent with the association between disgust and harsher moral judgments and suggest that disgust is antithetical to the building of trust. However, the association disappears if individuals are aware that their disgust is unrelated to the setting.

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The Glow Still Shows: Effects of Facial Masking on Perceptions of Duchenne Versus Social Smiles

Perception ◽

10.1177/03010066211027052 ◽

2021 ◽

pp. 030100662110270

Author(s):

Kennon M. Sheldon ◽

Ryan Goffredi ◽

Mike Corcoran

Keyword(s):

Facial Expressions ◽

Lower Half ◽

Communicative Functions ◽

The Face ◽

Facial Expressions Of Emotion ◽

Duchenne Smiles ◽

Neutral Expression

Facial expressions of emotion have important communicative functions. It is likely that mask-wearing during pandemics disrupts these functions, especially for expressions defined by activity in the lower half of the face. We tested this by asking participants to rate both Duchenne smiles (DSs; defined by the mouth and eyes) and non-Duchenne or “social” smiles (SSs; defined by the mouth alone), within masked and unmasked target faces. As hypothesized, masked SSs were rated much lower in “a pleasant social smile” and much higher in “a merely neutral expression,” compared with unmasked SSs. Essentially, masked SSs became nonsmiles. Masked DSs were still rated as very happy and pleasant, although significantly less so than unmasked DSs. Masked DSs and SSs were both rated as displaying more disgust than the unmasked versions.

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Emotion Recognition of Facial Expressions Presented in Profile

Psychological Reports ◽

10.1177/00332941211018403 ◽

2021 ◽

pp. 003329412110184

Author(s):

Paola Surcinelli ◽

Federica Andrei ◽

Ornella Montebarocci ◽

Silvana Grandi

Keyword(s):

Emotion Recognition ◽

Facial Expressions ◽

Response Times ◽

Recognition Accuracy ◽

Recognition Of Facial Expressions ◽

Profile View ◽

The Face ◽

Within Subjects ◽

Face Stimuli ◽

Affective Information

Aim of the research The literature on emotion recognition from facial expressions shows significant differences in recognition ability depending on the proposed stimulus. Indeed, affective information is not distributed uniformly in the face and recent studies showed the importance of the mouth and the eye regions for a correct recognition. However, previous studies used mainly facial expressions presented frontally and studies which used facial expressions in profile view used a between-subjects design or children faces as stimuli. The present research aims to investigate differences in emotion recognition between faces presented in frontal and in profile views by using a within subjects experimental design. Method The sample comprised 132 Italian university students (88 female, Mage = 24.27 years, SD = 5.89). Face stimuli displayed both frontally and in profile were selected from the KDEF set. Two emotion-specific recognition accuracy scores, viz., frontal and in profile, were computed from the average of correct responses for each emotional expression. In addition, viewing times and response times (RT) were registered. Results Frontally presented facial expressions of fear, anger, and sadness were significantly better recognized than facial expressions of the same emotions in profile while no differences were found in the recognition of the other emotions. Longer viewing times were also found when faces expressing fear and anger were presented in profile. In the present study, an impairment in recognition accuracy was observed only for those emotions which rely mostly on the eye regions.

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Neurogastronomy as a Tool for Evaluating Emotions and Visual Preferences of Selected Food Served in Different Ways

Foods ◽

10.3390/foods10020354 ◽

2021 ◽

Vol 10 (2) ◽

pp. 354

Author(s):

Jakub Berčík ◽

Johana Paluchová ◽

Katarína Neomániová

Keyword(s):

Eye Movements ◽

Air Quality ◽

Eye Tracking ◽

Facial Expressions ◽

Visual Design ◽

Personal Interview ◽

Visual Preferences ◽

New Perspective ◽

Corporate Resources ◽

Face Reading

The appearance of food provides certain expectations regarding the harmonization of taste, delicacy, and overall quality, which subsequently affects not only the intake itself but also many other features of the behavior of customers of catering facilities. The main goal of this article is to find out what effect the visual design of food (waffles) prepared from the same ingredients and served in three different ways—a stone plate, street food style, and a white classic plate—has on the consumer’s preferences. In addition to the classic tablet assistance personal interview (TAPI) tools, biometric methods such as eye tracking and face reading were used in order to obtain unconscious feedback. During testing, air quality in the room by means of the Extech device and the influence of the visual design of food on the perception of its smell were checked. At the end of the paper, we point out the importance of using classical feedback collection techniques (TAPI) and their extension in measuring subconscious reactions based on monitoring the eye movements and facial expressions of the respondents, which provides a whole new perspective on the perception of visual design and serving food as well as more effective targeting and use of corporate resources.

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The face of future: Face expressions during future thinking

Quarterly Journal of Experimental Psychology ◽

10.1177/1747021821992991 ◽

2021 ◽

pp. 174702182199299

Author(s):

Mohamad El Haj ◽

Emin Altintas ◽

Ahmed A Moustafa ◽

Abdel Halim Boudoukha

Keyword(s):

Facial Expression ◽

Facial Expressions ◽

Emotional Experience ◽

Future Scenarios ◽

Future Thinking ◽

Analysis Software ◽

Emotional Facial Expressions ◽

Facial Analysis ◽

The Face ◽

Face Expressions

Future thinking, which is the ability to project oneself forward in time to pre-experience an event, is intimately associated with emotions. We investigated whether emotional future thinking can activate emotional facial expressions. We invited 43 participants to imagine future scenarios, cued by the words “happy,” “sad,” and “city.” Future thinking was video recorded and analysed with a facial analysis software to classify whether facial expressions (i.e., happy, sad, angry, surprised, scared, disgusted, and neutral facial expression) of participants were neutral or emotional. Analysis demonstrated higher levels of happy facial expressions during future thinking cued by the word “happy” than “sad” or “city.” In contrast, higher levels of sad facial expressions were observed during future thinking cued by the word “sad” than “happy” or “city.” Higher levels of neutral facial expressions were observed during future thinking cued by the word “city” than “happy” or “sad.” In the three conditions, the neutral facial expressions were high compared with happy and sad facial expressions. Together, emotional future thinking, at least for future scenarios cued by “happy” and “sad,” seems to trigger the corresponding facial expression. Our study provides an original physiological window into the subjective emotional experience during future thinking.

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Facial Expression Recognition Based on Multi-Features Cooperative Deep Convolutional Network

Applied Sciences ◽

10.3390/app11041428 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1428

Author(s):

Haopeng Wu ◽

Zhiying Lu ◽

Jianfeng Zhang ◽

Xin Li ◽

Mingyue Zhao ◽

...

Keyword(s):

Facial Expression ◽

Facial Expressions ◽

Facial Expression Recognition ◽

Video Data ◽

Expression Recognition ◽

Convolutional Network ◽

Facial Movements ◽

The Face ◽

Deep Convolutional Network ◽

Selection Of

This paper addresses the problem of Facial Expression Recognition (FER), focusing on unobvious facial movements. Traditional methods often cause overfitting problems or incomplete information due to insufficient data and manual selection of features. Instead, our proposed network, which is called the Multi-features Cooperative Deep Convolutional Network (MC-DCN), maintains focus on the overall feature of the face and the trend of key parts. The processing of video data is the first stage. The method of ensemble of regression trees (ERT) is used to obtain the overall contour of the face. Then, the attention model is used to pick up the parts of face that are more susceptible to expressions. Under the combined effect of these two methods, the image which can be called a local feature map is obtained. After that, the video data are sent to MC-DCN, containing parallel sub-networks. While the overall spatiotemporal characteristics of facial expressions are obtained through the sequence of images, the selection of keys parts can better learn the changes in facial expressions brought about by subtle facial movements. By combining local features and global features, the proposed method can acquire more information, leading to better performance. The experimental results show that MC-DCN can achieve recognition rates of 95%, 78.6% and 78.3% on the three datasets SAVEE, MMI, and edited GEMEP, respectively.

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Hybrid Attention Cascade Network for Facial Expression Recognition

Sensors ◽

10.3390/s21062003 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2003 ◽

Cited By ~ 1

Author(s):

Xiaoliang Zhu ◽

Shihao Ye ◽

Liang Zhao ◽

Zhicheng Dai

Keyword(s):

Facial Expression ◽

Facial Expressions ◽

Facial Expression Recognition ◽

Expression Recognition ◽

Spatial Features ◽

Face Images ◽

Temporal Features ◽

The Face ◽

In The Wild ◽

Fusion Features

As a sub-challenge of EmotiW (the Emotion Recognition in the Wild challenge), how to improve performance on the AFEW (Acted Facial Expressions in the wild) dataset is a popular benchmark for emotion recognition tasks with various constraints, including uneven illumination, head deflection, and facial posture. In this paper, we propose a convenient facial expression recognition cascade network comprising spatial feature extraction, hybrid attention, and temporal feature extraction. First, in a video sequence, faces in each frame are detected, and the corresponding face ROI (range of interest) is extracted to obtain the face images. Then, the face images in each frame are aligned based on the position information of the facial feature points in the images. Second, the aligned face images are input to the residual neural network to extract the spatial features of facial expressions corresponding to the face images. The spatial features are input to the hybrid attention module to obtain the fusion features of facial expressions. Finally, the fusion features are input in the gate control loop unit to extract the temporal features of facial expressions. The temporal features are input to the fully connected layer to classify and recognize facial expressions. Experiments using the CK+ (the extended Cohn Kanade), Oulu-CASIA (Institute of Automation, Chinese Academy of Sciences) and AFEW datasets obtained recognition accuracy rates of 98.46%, 87.31%, and 53.44%, respectively. This demonstrated that the proposed method achieves not only competitive performance comparable to state-of-the-art methods but also greater than 2% performance improvement on the AFEW dataset, proving the significant outperformance of facial expression recognition in the natural environment.

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The Effect of State Gratitude on Cognitive Flexibility: A Within-Subject Experimental Approach

Brain Sciences ◽

10.3390/brainsci10070413 ◽

2020 ◽

Vol 10 (7) ◽

pp. 413

Author(s):

Andree Hartanto ◽

Nadia C. H. Ong ◽

Wee Qin Ng ◽

Nadyanna M. Majeed

Keyword(s):

Pilot Study ◽

Cognitive Functioning ◽

Cognitive Flexibility ◽

Positive Emotion ◽

Positive Emotions ◽

Experimental Approach ◽

Main Study ◽

Considerable Research ◽

Potential Benefits ◽

The Relationship

Considerable research has examined the relationship between positive emotion and cognitive flexibility. Less is known, however, about the causal relationship between discrete positive emotions, specifically gratitude, and cognitive flexibility. Given that different positive emotions may dissimilarly affect cognitive functioning, we sought to examine the effect of state gratitude on cognitive flexibility. A pilot study with ninety-five participants was employed to ensure the effectiveness of our gratitude manipulation. One hundred and thirteen participants were recruited for the main study, which utilized a within-subject experimental approach. After the manipulation, participants completed a well-established task-switching paradigm, which was used to measure cognitive flexibility. Contrary to our hypotheses, we did not find any evidence that state gratitude may enhance cognitive flexibility. The current study identified some boundary conditions around the potential benefits of the experience of gratitude.

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Evidence from young children regarding emotional responses to music

Behavioral and Brain Sciences ◽

10.1017/s0140525x08005360 ◽

2008 ◽

Vol 31 (5) ◽

pp. 581-582 ◽

Cited By ~ 2

Author(s):

Steven John Holochwost ◽

Carroll E. Izard

Keyword(s):

Pilot Study ◽

Young Children ◽

Facial Expressions ◽

Emotional Response ◽

Emotional Responses ◽

Theoretical Framework ◽

Future Research

AbstractJuslin & Västfjäll (J&V) propose a theoretical framework of how music may evoke an emotional response. This commentary presents results from a pilot study that employed young children as participants, and measured musically induced emotions through facial expressions. Preliminary findings support certain aspects of the proposed theoretical framework. The implications of these findings on future research employing the proposed framework are discussed.

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