An environment for studying visual emotion perception

Visual emotion perception is the ability of recognizing and identifying emotions through the visual interpretation of a situation or environment. In this paper we propose an innovative environment for supporting this type of studies, aimed at replacing current pencil-and-paper approaches. Besides automatizing the whole process, this environment provides new features that can enrich the study of emotion perception. These new features are especially interesting for the field of Human-Compute Interaction and Affective computing as they quantify the effects of experiencing different emotional dimensions on the individual’s interaction with the computer.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Social perception in the real world : employing visual adaptation paradigms in the investigation of mechanisms underlying emotion and trustworthiness perception

Social context can substantially influence our perception and understanding of emotion and action of observed individuals. However, less is known about how temporal context can affect our judgement of behaviour of other people. The aim of this thesis was to explore how immediate perceptual history influences social perception. Further aims were: (i) to examine whether prior visual experience influences the perception of behaviour of other individuals in a naturalistic virtual environment resembling the real world; (ii) to determine whether our judgement of emotional state or trustworthiness of observed individuals is influenced by perceptual history, and (iii) by cognitive processes such as mental state attribution to the observer; (iv) to investigate whether processing of emotion information from dynamic, whole-body action is dependent on the processing of body identity, and (v) dependent on the body part that conveys it. Here, visual adaptation paradigms were used to examine systematic biases in social perception following prior visual experience, and to infer potential neural mechanisms underlying social perception. The results presented in this thesis suggest that perception and understanding of behaviour of other individuals in the naturalistic virtual environment are influenced by the behaviour of other individuals within the shared social environment. Specifically, in Chapter 3, I presented data suggesting that visual adaptation mechanisms examined thus far in laboratory settings may influence our everyday perception and judgement of behaviour of other people. In Chapters 4 and 5, I showed that these biases in social perception can be attributed to visual adaptation mechanisms, which code emotions and intentions derived from actions with respect to specific action kinematics and the body part that conveyed the given emotion. The results of experiments presented in Chapter 4 demonstrated that emotions conveyed by actions are represented with respect to, and independently of, actors’ identity. These finding suggest that the mechanisms underlying processing of action emotion may operate in parallel with the mechanisms underlying processing emotion from other social signals such as face and voice. In Chapter 6, I showed that cognitive processes underlying Theory of Mind, such as mental state attribution, can also influence perceptual processing of emotional signals. Finally, results presented in Chapter 7 suggest that judgments of complex social traits such as trustworthiness derived from faces are also influenced by perceptual history. These results also yielded strong sex differences in assessing trustworthiness of an observed individual; female observers showed a strong bias in perception resulting from adaptation to (un)trustworthiness, while male observers were less influenced by prior visual context. Together these findings suggest that social perception in the real world may be sensitive not only to the social context in which an observed act is embedded, but also to the prior visual context and the observer’s beliefs regarding the observed individual. Visual adaptation mechanisms may therefore operate during our everyday perception, in order to adjust our visual system to allow for efficient and accurate judgement of socially meaningful stimuli. The findings presented in this thesis highlight the importance of studying social perception using naturalistic stimuli embedded in a meaningful social scene, in order to gain a better understanding of the mechanisms that underlie our judgement of behaviour of other people. They also demonstrate the utility of visual adaptation paradigms in studying social perception and social cognition

Situating emotional experience

Psychological construction approaches to emotion suggest that emotional experience is situated and dynamic. Fear, for example, is typically studied in a physical danger context (e.g., threatening snake), but in the real world, it often occurs in social contexts, especially those involving social evaluation (e.g., public speaking). Understanding situated emotional experience is critical because adaptive responding is guided by situational context (e.g., inferring the intention of another in a social evaluation situation vs. monitoring the environment in a physical danger situation). In an fMRI study, we assessed situated emotional experience using a newly developed paradigm in which participants vividly imagine different scenarios from a first-person perspective, in this case scenarios involving either social evaluation or physical danger. We hypothesized that distributed neural patterns would underlie immersion in social evaluation and physical danger situations, with shared activity patterns across both situations in multiple sensory modalities and in circuitry involved in integrating salient sensory information, and with unique activity patterns for each situation type in coordinated large-scale networks that reflect situated responding. More specifically, we predicted that networks underlying the social inference and mentalizing involved in responding to a social threat (in regions that make up the “default mode” network) would be reliably more active during social evaluation situations. In contrast, networks underlying the visuospatial attention and action planning involved in responding to a physical threat would be reliably more active during physical danger situations. The results supported these hypotheses. In line with emerging psychological construction approaches, the findings suggest that coordinated brain networks offer a systematic way to interpret the distributed patterns that underlie the diverse situational contexts characterizing emotional life

Define design thinking

No abstract available

First impressions: A survey on vision-based apparent personality trait analysis

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Personality analysis has been widely studied in psychology, neuropsychology, and signal processing fields, among others. From the past few years, it also became an attractive research area in visual computing. From the computational point of view, by far speech and text have been the most considered cues of information for analyzing personality. However, recently there has been an increasing interest from the computer vision community in analyzing personality from visual data. Recent computer vision approaches are able to accurately analyze human faces, body postures and behaviors, and use these information to infer apparent personality traits. Because of the overwhelming research interest in this topic, and of the potential impact that this sort of methods could have in society, we present in this paper an up-to-date review of existing vision-based approaches for apparent personality trait recognition. We describe seminal and cutting edge works on the subject, discussing and comparing their distinctive features and limitations. Future venues of research in the field are identified and discussed. Furthermore, aspects on the subjectivity in data labeling/evaluation, as well as current datasets and challenges organized to push the research on the field are reviewed.Peer ReviewedPostprint (author's final draft

An Integrative Neurological Model for Basic Observable Human Behavior

The scientific method uncovers information from the natural world in small increments. This spurs the design of models to explain how the pieces fit together and to identify future targets of research. This is especially the case in psychology, where visualizing concepts is an advantageous practice. One all too common criticism of cognitive and behavioral models in psychology is the lack of a biological basis. This paper aims to alleviate part of this issue by integrating currently understood biological and neurological mechanisms that drive psychological phenomena into a predictive and descriptive model for basic human behavior. To accomplish this task, this paper explores numerous scientific reviews and studies regarding sensory perception, emotion, learning, and memory. This paper also features original research about decision making. Creating this model is a necessary first step for targeting possible future research and clinical practices related to human behavior

Evolution, Consciousness, and the Internality of Mind

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