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

Dissociation and interpersonal autonomic physiology in psychotherapy research: an integrative view encompassing psychodynamic and neuroscience theoretical frameworks

Interpersonal autonomic physiology is an interdisciplinary research field, assessing the relational interdependence of two (or more) interacting individual both at the behavioral and psychophysiological levels. Despite its quite long tradition, only eight studies since 1955 have focused on the interaction of psychotherapy dyads, and none of them have focused on the shared processual level, assessing dynamic phenomena such as dissociation. We longitudinally observed two brief psychodynamic psychotherapies, entirely audio and video-recorded (16 sessions, weekly frequency, 45 min.). Autonomic nervous system measures were continuously collected during each session. Personality, empathy, dissociative features and clinical progress measures were collected prior and post therapy, and after each clinical session. Two-independent judges, trained psychotherapist, codified the interactions\u2019 micro-processes. Time-series based analyses were performed to assess interpersonal synchronization and de-synchronization in patient\u2019s and therapist\u2019s physiological activity. Psychophysiological synchrony revealed a clear association with empathic attunement, while desynchronization phases (range of length 30-150 sec.) showed a linkage with dissociative processes, usually associated to the patient\u2019s narrative core relational trauma. Our findings are discussed under the perspective of psychodynamic models of Stern (\u201cpresent moment\u201d), Sander, Beebe and Lachmann (dyad system model of interaction), Lanius (Trauma model), and the neuroscientific frameworks proposed by Thayer (neurovisceral integration model), and Porges (polyvagal theory). The collected data allows to attempt an integration of these theoretical approaches under the light of Complex Dynamic Systems. The rich theoretical work and the encouraging clinical results might represents a new fascinating frontier of research in psychotherapy

Left threatened by Right: political intergroup bias in the contemporary Italian context.

Using different evaluation targets (i.e., politicians’ pictures, ideological words, items referring to features attributed to political ingroup/outgroup) we characterized the intergroup bias among political groups in the Italian context (Study 1-2-3) and tested a model that may account for the bias itself (Study 3). For all evaluation targets, left-wing participants -compared to right wing participants - showed a greater intergroup bias, expressing more negative emotions towards the outgroup. The process was influenced by a greater perceived threat of the outgroup. Conversely, right-wing participants expressed the bias only when presented with ideological words. Our results provide a detailed description of how intergroup bias in Italy is differently expressed by the two ideological groups depending on the targets used to represent the political counterpart. Moreover, the results show that the stronger bias expressed by left-wing participants is driven by perceived threat of the outgroup

The attracting power of the gaze of politicians is modulated by the personality and ideological attitude of their voters: a functional magnetic resonance imaging study.

Observing someone rapidly moving their eyes induces reflexive shifts of overt and covert attention in the onlooker. Previous studies have shown that this process can be modulated by the onlooker's personality, as well as by the social features of the person depicted in the cued face. Here, we investigated whether an individual's preference for social dominance orientation, in-group perceived similarity (PS), and political affiliation of the cued-face modulated neural activity within specific nodes of the social attention network. During functional magnetic resonance imaging, participants were requested to perform a gaze-following task to investigate whether the directional gaze of various Italian political personages might influence the oculomotor behaviour of in-group or out-group voters. After scanning, we acquired measures of PS in personality traits with each political personage and preference for social dominance orientation. Behavioural data showed that higher gaze interference for in-group than out-group political personages was predicted by a higher preference for social hierarchy. Higher blood oxygenation level-dependent activity in incongruent vs. congruent conditions was found in areas associated with orienting to socially salient events and monitoring response conflict, namely the left frontal eye field, right supramarginal gyrus, mid-cingulate cortex and left anterior insula. Interestingly, higher ratings of PS with the in-group and less preference for social hierarchy predicted increased activity in the left frontal eye field during distracting gaze movements of in-group as compared with out-group political personages. Our results suggest that neural activity in the social orienting circuit is modulated by higher-order social dimensions, such as in-group PS and individual differences in ideological attitudes

The distracted robot: what happens when artificial agents behave like us

In everyday life, we are frequently exposed to different smart technologies. From our smartphones to avatars in computer games, and soon perhaps humanoid robots, we are surrounded by artificial agents created to interact with us. Already during the design phase of an artificial agent, engineers often endow it with functions aimed to promote the interaction and engagement with it, ranging from its \u201ccommunicative\u201d abilities to the movements it produces. Still, whether an artificial agent that can behave like a human could boost the spontaneity and naturalness of interaction is still an open question. Even during the interaction with conspecifics, humans rely partially on motion cues when they need to infer the mental states underpinning behavior. Similar processes may be activated during the interaction with embodied artificial agents, such as humanoid robots. At the same time, a humanoid robot that can faithfully reproduce human-like behavior may undermine the interaction, causing a shift in attribution: from being endearing to being uncanny. Furthermore, it is still not clear whether individual biases and prior knowledge related to artificial agents can override perceptual evidence of human-like traits. A relatively new area of research emerged in the context of investigating individuals\u2019 reactions towards robots, widely referred to as Human-Robot Interaction (HRI). HRI is a multidisciplinary community that comprises psychologists, neuroscientists, philosophers as well as roboticists, and engineers. However, HRI research has been often based on explicit measures (i.e. self-report questionnaires, a-posteriori interviews), while more implicit social cognitive processes that are elicited during the interaction with artificial agents took second place behind more qualitative and anecdotal results. The present work aims to demonstrate the usefulness of combining the systematic approach of cognitive neuroscience with HRI paradigms to further investigate social cognition processes evoked by artificial agents. Thus, this thesis aimed at exploring human sensitivity to anthropomorphic characteristics of a humanoid robot's (i.e. iCub robot) behavior, based on motion cues, under different conditions of prior knowledge. To meet this aim, we manipulated the human-likeness of the behaviors displayed by the robot and the explicitness of instructions provided to the participants, in both screen-based and real-time interaction scenarios. Furthermore, we explored some of the individual differences that affect general attitudes towards robots, and the attribution of human-likeness consequently

STVARANJE PROMOCIJSKE PORUKE: ISTRAŽIVANJE ULOGE NEVERBALNE KOMUNIKACIJE U OGLAŠAVANJU

The purpose of this paper is to explore the influences of different nonverbal elements, which are related to both products and personal characteristics, on individuals\u27 perception of products advertised. Nonverbal elements augment the communication message that particular product or service aims to deliver to its target audience. Empirical research is conducted using two different sets of commercials, i.e. comparing video and static commercials for three different products in a fast consumer moving goods category. The research results indicate that the role of nonverbal communication is repeating, conflicting, replacing and highlighting or mitigating the verbal component of a communication message. In an advertisement equal attention should be addressed to both verbal and nonverbal communication components. Depending on the product category, non-verbal communication contributes to a greater or a lesser extent, but always in positive way in evaluating characteristics of the person that uses the advertised product. Non-verbal communication, therefore can be used to augment the desired brand perception. Managerial implications are also considered.Svrha ovog članka je istražiti utjecaje različitih neverbalnih elemenata na percepciju karakteristika proizvoda i percepciju osobnih karakteristika pojedinca koji upotrebljavaju oglašavani proizvod. Neverbalni elementi pojačavaju komunikacijsku poruku koju određeni proizvod ili usluga želi prenijeti ciljnoj publici. Empirijsko istraživanje provedeno je na dvije skupine oglasa, odnosno uspoređuju se videooglasi i statični oglasi za tri različita proizvoda u kategoriji proizvoda brze potrošnje. Rezultati istraživanja ukazuju da je uloga neverbalne komunikacije u ponavljanju, proturječju, dopunjivanju, isticanju ili ublažavanju verbalne komponente kôd komunikacijske poruke. Prilikom stvaranja oglasa podjednaka pažnja bi se trebala pridavati i verbalnoj i neverbalnoj komunikacijskoj komponenti. Ovisno o kategoriji proizvoda neverbalna komunikacija u većoj ili manjoj mjeri, ali uvijek pozitivno, utječe na percepciju karakteristika osobe koja koristi oglašavani proizvod. Neverbalna komunikacija stoga može se koristiti kako bi se povećala željena percepcija oglašavanje marke. Implikacije za menadžere također su ponuđene

Driver Trust in Automated Driving Systems

Vehicle automation is a prominent example of safety-critical AI-based task automation. Recent digital innovations have led to the introduction of partial vehicle automation, which can already give vehicle drivers a sense of what fully automated driving would feel like. In the context of current imperfect vehicle automation, establishing an appropriate level of driver trust in automated driving systems (ADS) is seen as a key factor for their safe use and long-term acceptance. This paper thoroughly reviews and synthesizes the literature on driver trust in ADS, covering a wide range of academic disciplines. Pulling together knowledge on trustful user interaction with ADS, this paper offers a first classification of the main trust calibrators. Guided by this analysis, the paper identifies a lack of studies on adaptive, contextual trust calibration in contrast to numerous studies that focus on general trust calibration

Prediction of uncertainty events using human-computer interaction

The practice of medicine is characterized by complex situations that evoke uncertainty. Uncertainty has implications for the quality and costs of health care, thus emphasizing the importance of identifying its the main causes. Uncertainty can be manifested through human behaviour. Accordingly, in this dissertation, a machine learning model that detects events of uncertainty based on mouse cursor movements was created. To do so, 79 participants answered an online survey while the mouse data was being tracked. This data was used to extract meaningful features that allowed model testing and training after a feature selection stage. With the implementation of a Logistic Regression, and applying a k-fold cross-validation method, the model achieved an estimated performance of 81%. It was found that, during moments of uncertainty, the number of horizontal direction inversions increases and the mouse cursor travels higher distances. Moreover, items that evoke uncertainty are associated to longer interaction times and a higher number of visits. Subsequently, the model was applied to a medical decision making task performed by 8 physicians, in order to understand whether it might be applied in different contexts or not. The results were consistent with the task design. To better understand the nature of uncertainty, its relationship with personality was explored. Regarding the clinical task, it was found a slight tendency of uncertainty to increase with Neuroticism. In the future, the created model may be used to help physicians understand their main difficulties

Using social robots to encourage honest behaviours

This thesis presents a series of studies to understand if robots can promote more honest behaviours from people, when they are tempted to behave dishonestly. In Study 1 we see that a robot just presenting gaze behaviour inhibits cheating, but a robot doing small talk, does not. In Study 2 we see that participants cheated to an equal extent when doing the task in their homes alone or with a video of a robot looking at them. In Study 3 we find that including situation awareness in a robot (showing awareness of the participant behaviour), decreased cheating across the game. In Study 4 we see that priming participants for their relational self-concept does not enhance the situation awareness effect on cheating. In study 5 and 6 we explore participants perceptions, and we see that people consider it wrong to be dishonest towards a robot. However, they would feel low levels of guilt and justify it by the robots’ lack of capabilities, presence, and a human tendency for dishonesty. When prompted to evaluate what other’s/or their own attitudes would be regarding dishonesty, manipulating the caring behaviour of a robot, it shows no effect and people in general think others would be dishonest and hold themselves in a more neutral stance. Interestingly, people that show more negative attitudes towards robots tend to report that others will act more dishonestly as well as themselves. These are important considerations for the development of robots, in the future, to work alongside with humans.Esta tese apresenta uma série de estudos para perceber se os robôs podem promover comportamentos honestos nas pessoas. No Estudo 1 observa-se que um robô que apenas olha para o utilizador, inibe batota, mas um robô que apresenta algum comportamento verbal não tem o mesmo efeito. No estudo 2, vemos que os participantes fazem batota tanto sozinhos, nas suas casas, como na presença de um vídeo de um robô que simplesmente olha. No Estudo 3 incluindo no robô a capacidade de perceber as jogadas dos participantes e reagir a elas, diminui a batota ao longo do jogo. No Estudo 4 a inclusão de um priming para o auto-conceito relacional não aumenta o efeito encontrado no Estudo 3. Finalmente, no Estudo 5 e 6 exploram-se as perceções das pessoas, e verifica-se que consideram errado ser-se desonesto com um robô, mas reportando baixos níveis de culpa. Justificam a desonestidade por: falta de capacidades no robô, falta de presença e a existência de uma tendência humana para a desonestidade. Quando avaliadas as atitudes que os outros teriam ou eles próprios em ser-se desonesto, manipulando o carácter afetivo do robô, não existem efeitos e as pessoas no geral reportam que os outros serão desonestos mantendo-se a si mesmas numa posição neutra. Curiosamente, os que demonstram atitudes mais negativas face a interagirem com robôs, reportam mais desonestidade. Estas são considerações importantes para o desenvolvimento de robôs para colaborarem com humanos no futuro

Judgements of a speaker’s personality are correlated across differing content and stimulus type

It has previously been shown that first impressions of a speaker’s personality, whether accurate or not, can be judged from short utterances of vowels and greetings, as well as from prolonged sentences and readings of complex paragraphs. From these studies, it is established that listeners’ judgements are highly consistent with one another, suggesting that different people judge personality traits in a similar fashion, with three key personality traits being related to measures of valence (associated with trustworthiness), dominance, and attractiveness. Yet, particularly in voice perception, limited research has established the reliability of such personality judgements across stimulus types of varying lengths. Here we investigate whether first impressions of trustworthiness, dominance, and attractiveness of novel speakers are related when a judgement is made on hearing both one word and one sentence from the same speaker. Secondly, we test whether what is said, thus adjusting content, influences the stability of personality ratings. 60 Scottish voices (30 females) were recorded reading two texts: one of ambiguous content and one with socially-relevant content. One word (~500 ms) and one sentence (~3000 ms) were extracted from each recording for each speaker. 181 participants (138 females) rated either male or female voices across both content conditions (ambiguous, socially-relevant) and both stimulus types (word, sentence) for one of the three personality traits (trustworthiness, dominance, attractiveness). Pearson correlations showed personality ratings between words and sentences were strongly correlated, with no significant influence of content. In short, when establishing an impression of a novel speaker, judgments of three key personality traits are highly related whether you hear one word or one sentence, irrespective of what they are saying. This finding is consistent with initial personality judgments serving as elucidators of approach or avoidance behaviour, without modulation by time or content. All data and sounds are available on OSF (osf.io/s3cxy)