Emoções faciais desempenham um papel fundamental nas relações interpessoais humanas. Certas doenças psiquiátricas podem se caracterizar por déficits no reconhecimento das emoções. Nesse contexto, o presente projeto faz parte de um projeto maior que visa a desenvolver um jogo sério para auxílio ao diagnóstico e treinamento no reconhecimento de expressões faciais utilizando grafos And-Or para representação de emoções. Este projeto de mestrado define, implementa e avalia uma abordagem que gera caricaturas de várias emoções faciais (satisfação, tristeza, surpresa, medo, aversão, raiva e neutra) a partir de imagens de treinamento. Foi desenvolvida uma metodologia de processamento de imagens que localiza pontos de controle faciais em imagens reais de pessoas expressando as diferentes emoções, e aprende as variações de todos os pontos de controle, da face neutra para uma determinada emoção, para caracterização das expressões faciais. Para poder comparar a fidelidade da representação da emoção desejada nas imagens geradas, com respeito a uma abordagem anterior (que utiliza antropometria e FACS - Facial Action Coding System), um experimento com voluntários foi conduzido. Os resultados mostraram que a taxa de reconhecimento das imagens geradas com a metodologia proposta neste projeto, em relação às imagens geradas com a metodologia anterior, foi inferior em cinco emoções (medo, raiva, satisfação, surpresa e tristeza), igual para uma emoção (neutra) e superior para uma emoção (aversão). Para a emoção de aversão, cuja taxa de reconhecimento foi superior na abordagem proposta neste projeto, conseguiu-se aprender variações significativas de pontos de controle que não estão presentes nas unidades de ação que o FACS prevê para essa emoção. Esses dados sugerem que a proposta de aprender as variações de todos os pontos de controle da face pode ajudar em representar melhor as emoções faciais. Foram identificadas as possíveis causas para as taxas de reconhecimento inferiores das cinco emoções citadas, tanto na seleção da amostra de treinamento quanto nas etapas de processamento de imagens, as quais podem ser aperfeiçoadas a fim de melhorar a geração das caricaturas. Portanto, os resultados indicam que a abordagem apresentada é promissora, uma vez que considera todos os pontos de controle identificados em imagens reais e que o aperfeiçoamento de algumas fases do processo pode gerar caricaturas mais próximas das expressões reais, considerando diferentes intensidades das emoções / Facial emotions play a key role in human interpersonal relationships. Some psychiatric disorders may be characterized by deficits in recognizing emotions. In this context, this project is part of a major project that aims to develop a serious game to aid diagnosis and training in the recognition of facial expressions using And-Or graphs to emotions representing. This master\'s project defines, implements and evaluates an approach for generating caricatures of facial emotions (satisfaction, sadness, surprise, fear, disgust, anger, neutral) from training images. An image processing method that locates facial points in facial expression images was developed, and learns the variations of all facial points, from neutral face to a particular emotion for facial expression characterization. In order to compare the fidelity representation of the desired emotion in images generated with respect to anterior approach (using Anthropometry and Facial Action Coding System FACS), an experiment with volunteers was conducted. The rate recognition results showed that images generated with the proposed approach, compared to previous approach, were lower in five emotions (fear, anger, satisfaction, surprise and sadness), same to an emotion (neutral) and higher to an emotion (disgust). For disgust emotion, it was possible to learn significant variations of facial points that are not present in the action units that FACS provides for that emotion. This data suggests that the proposal for learning the variations of all facial points may help the facial emotion characterization. Possible causes for the lower rates were identified, both in the selection of training sample images and steps of image processing, which can be optimized in order to enhance the generation of caricatures. Therefore, the results indicate this approach is promising, since considers all facial points, and the improvement of some stages of the process can generate closest caricatures of real expressions, considering different intensities of emotions

Emoções faciais desempenham um papel fundamental nas relações interpessoais humanas. Certas doenças psiquiátricas podem se caracterizar por déficits no reconhecimento das emoções. Nesse contexto, o presente projeto faz parte de um projeto maior que visa a desenvolver um jogo sério para auxílio ao diagnóstico e treinamento no reconhecimento de expressões faciais utilizando grafos And-Or para representação de emoções. Este projeto de mestrado define, implementa e avalia uma abordagem que gera caricaturas de várias emoções faciais (satisfação, tristeza, surpresa, medo, aversão, raiva e neutra) a partir de imagens de treinamento. Foi desenvolvida uma metodologia de processamento de imagens que localiza pontos de controle faciais em imagens reais de pessoas expressando as diferentes emoções, e aprende as variações de todos os pontos de controle, da face neutra para uma determinada emoção, para caracterização das expressões faciais. Para poder comparar a fidelidade da representação da emoção desejada nas imagens geradas, com respeito a uma abordagem anterior (que utiliza antropometria e FACS - Facial Action Coding System), um experimento com voluntários foi conduzido. Os resultados mostraram que a taxa de reconhecimento das imagens geradas com a metodologia proposta neste projeto, em relação às imagens geradas com a metodologia anterior, foi inferior em cinco emoções (medo, raiva, satisfação, surpresa e tristeza), igual para uma emoção (neutra) e superior para uma emoção (aversão). Para a emoção de aversão, cuja taxa de reconhecimento foi superior na abordagem proposta neste projeto, conseguiu-se aprender variações significativas de pontos de controle que não estão presentes nas unidades de ação que o FACS prevê para essa emoção. Esses dados sugerem que a proposta de aprender as variações de todos os pontos de controle da face pode ajudar em representar melhor as emoções faciais. Foram identificadas as possíveis causas para as taxas de reconhecimento inferiores das cinco emoções citadas, tanto na seleção da amostra de treinamento quanto nas etapas de processamento de imagens, as quais podem ser aperfeiçoadas a fim de melhorar a geração das caricaturas. Portanto, os resultados indicam que a abordagem apresentada é promissora, uma vez que considera todos os pontos de controle identificados em imagens reais e que o aperfeiçoamento de algumas fases do processo pode gerar caricaturas mais próximas das expressões reais, considerando diferentes intensidades das emoções / Facial emotions play a key role in human interpersonal relationships. Some psychiatric disorders may be characterized by deficits in recognizing emotions. In this context, this project is part of a major project that aims to develop a serious game to aid diagnosis and training in the recognition of facial expressions using And-Or graphs to emotions representing. This master\'s project defines, implements and evaluates an approach for generating caricatures of facial emotions (satisfaction, sadness, surprise, fear, disgust, anger, neutral) from training images. An image processing method that locates facial points in facial expression images was developed, and learns the variations of all facial points, from neutral face to a particular emotion for facial expression characterization. In order to compare the fidelity representation of the desired emotion in images generated with respect to anterior approach (using Anthropometry and Facial Action Coding System FACS), an experiment with volunteers was conducted. The rate recognition results showed that images generated with the proposed approach, compared to previous approach, were lower in five emotions (fear, anger, satisfaction, surprise and sadness), same to an emotion (neutral) and higher to an emotion (disgust). For disgust emotion, it was possible to learn significant variations of facial points that are not present in the action units that FACS provides for that emotion. This data suggests that the proposal for learning the variations of all facial points may help the facial emotion characterization. Possible causes for the lower rates were identified, both in the selection of training sample images and steps of image processing, which can be optimized in order to enhance the generation of caricatures. Therefore, the results indicate this approach is promising, since considers all facial points, and the improvement of some stages of the process can generate closest caricatures of real expressions, considering different intensities of emotions

Childhood emotional maltreatment is associated with damaging consequences, although relatively little is known about the mechanisms underlying its effects. This dissertation investigated the concurrent influences of adult attachment and mindfulness on internalizing symptoms and emotional processing in young adults with and without a history of emotional maltreatment. Study 1 revealed that a sequential mediation model, with adult attachment orientations as first-step mediators and mindfulness as a second-step mediator, fit the data better than a simultaneous mediation model. In addition, moderation analyses revealed that high self-reported levels of mindfulness protected against the development of internalizing symptoms, even in at-risk individuals. Study 2 replicated these findings in a new sample, while also extending the results beyond a self-report outcome, using behavioural measures of emotional processing. Emotional maltreatment, adult attachment, and mindfulness predicted the amount of perceptual information required to correctly identify fearful faces and the amount of interference demonstrated in response to positive and negative emotional words. Cumulatively, these findings suggest that childhood emotional maltreatment can disrupt attachment relationships and encumber the development of mindfulness, contributing to internalizing symptoms and the biased processing of emotional information. However, alternative outcomes are possible, given the presence of high levels of mindfulness and secure attachment representations. This has implications for clarifying developmental theories and evaluating clinical interventions that may mitigate the negative effects of childhood emotional maltreatment.

<div> <p>The purpose of this research was to examine the perception of micro-expressions in animated characters with different visual styles. Specifically, the work reported in this thesis sought to examine: (1) whether people can recognize micro-expressions in animated characters, (2) whether there are differences in recognition based on the character visual style (stylized versus realistic), (3) the extent to which the degree of exaggeration of micro-expressions affect the perceived naturalness and intensity of the animated characters’ emotion, and (4) whether there are differences in effects on perceived naturalness and intensity based on the character visual style. The research work involved two experiments: a recognition study and an emotion rating study. A total of 275 participants participated in both experiments. In the recognition study, the participants watched eight micro-expression animations representing four different emotions (happy, sad, fear, surprised). Four animations featured a stylized character and four a realistic character. For each animation, subjects were asked to identify the character’s emotion conveyed by the micro-expression. Results showed that all four emotions for both characters were recognized with an acceptable degree of accuracy. The recognition rates of the stylized character were 84.73% for happiness, 88.73% for sadness, 60.73% for fear, and 83.64% surprise. The recognition rates of the realistic character were 87.37% for happiness, 82.94% for sadness, 69.62% for fear, and 77.13% for surprise. In the emotion rating study, participants watched two sets of eight animation clips (16 clips in total). Eight animations in each set featured the character performing both macro- and micro-expressions, the different between these two sets was the exaggeration degree of micro-expressions (normal vs exaggerated). Participants were asked to recognize the character’s true emotion (conveyed by the micro-expressions) and rate the naturalness and intensity of the character’s emotion in each clip using a 5-point Likert scale. Findings showed that the <b>degree of exaggeration of the micro-expressions </b>had a significant effect on <b>emotion’s</b> <b>naturalness rating</b>, <b>emotion’s</b> <b>intensity rating</b>, and <b>true emotion recognition</b> and the <b>character visual style</b> had a significant effect on emotion’s <b>intensity rating</b>. Emotion type, participant gender and participant animation experience also had significant effects on perception of the micro-expression.</p> </div> <br>

Attention to emotions and emotional clarity are core dimensions of individual differences in emotion awareness. Findings from prior research based on self-report indicate that attention to and recognition of one’s own emotions are related to attention to and recognition of other people’s emotions. In the present experimental study, we examined the relations of attention to and clarity of emotions with the efficiency of facial affect perception. Moreover, it was explored whether attention to and clarity of emotions are linked to negative interpretations of facial expressions. A perception of facial expressions (PFE) task based on schematic faces with neutral, ambiguous, or unambiguous emotional expressions and a gender decision task were administered to healthy individuals along with measures of emotion awareness, state and trait anxiety, depression, and verbal intelligence. Participants had to decide how much the faces express six basic affects. Evaluative ratings and decision latencies were analyzed. Attention to feelings was negatively correlated with evaluative decision latency, whereas clarity of feelings was not related to decision latency in the PFE task. Attention to feelings was positively correlated with the perception of negative affects in ambiguous faces. Attention to feelings and emotional clarity were not related to gender decision latency. According to our results, dispositional attention to feelings goes along with an enhanced efficiency of facial affect perception. Habitually paying attention to one’s own emotions may facilitate processing of external emotional information. Preliminary evidence was obtained suggesting a relationship of dispositional attention to feelings with negative interpretations of facial expressions.