Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future

Coherence between subjective experience and physiology in emotion: Individual differences and implications for well-being.

Emotion theorists have characterized emotions as involving coherent responding across various emotion response systems (e.g., covariation of subjective experience and physiology). Greater response system coherence has been theorized to promote well-being, yet very little research has tested this assumption. The current study examined whether individuals with greater coherence between physiology and subjective experience of emotion report greater well-being. We also examined factors that may predict the magnitude of coherence, such as emotion intensity, cognitive reappraisal, and expressive suppression. Participants (N = 63) completed self-report measures of well-being, expressive suppression, and cognitive reappraisal. They then watched a series of emotionally evocative film clips designed to elicit positive and negative emotion. During the films, participants continuously rated their emotional experience using a rating dial, and their autonomic physiological responses were recorded. Time-lagged cross-correlations were used to calculate within-participant coherence between intensity of emotional experience (ranging from neutral to very negative or very positive) and physiology (composite of cardiac interbeat interval, skin conductance, ear pulse transit time, finger pulse transit time and amplitude, systolic and diastolic blood pressure). Results indicated that individuals with greater coherence reported greater well-being. Coherence was highest during the most emotionally intense film and among individuals who reported lower expressive suppression. However, coherence was not associated with reappraisal. These findings provide support for the idea that greater emotion coherence promotes well-being and also shed light on factors that are associated with the magnitude of coherence. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

Functional smiles: tools for love, sympathy, and war

The smile is the most frequent facial expression, but not all smiles are equal. A social functional account holds that smiles of reward, affiliation, and dominance resolve basic social tasks, including rewarding behavior, social bonding, and hierarchy negotiation. Here we explore facial expression patterns associated with the three smiles. We modeled the expressions using a data-driven approach and showed that reward smiles are symmetrical and accompanied by eyebrow raising, affiliative smiles involve lip pressing, and asymmetrical dominance smiles contain nose wrinkling and upper lip raising. A Bayesian classifier analysis and a detection task revealed that the three smile types are highly distinct facial expressions. Finally, social judgments made by a separate participant group showed that the different smile type models convey different social messages. Our results provide the first detailed description of the physical form and social messages conveyed by the three functional smiles, documenting the versatility of these facial expressions

Inhibitory Processing of Sad Facial Expressions and Depression Vulnerability

Depression vulnerability has been frequently linked to selective attention biases, but these biases may partly result from an inhibitory deficit for processing depressive information (Joormann, 2004). Reduced inhibition when encountering sad interpersonal information (e.g., faces) could lead to greater associative processing, deeper encoding among related depressive content in memory, increased rumination, and perhaps could promote depressive episodes. Inhibition and selective attention can be examined through behavioral and psychophysiological indicators, including the N200, P300a, and P300b ERP components. The present study examined whether groups traditionally at risk of depression would show inhibitory deficits for depressive facial expressions as compared to a low-risk group. A 2 x 2 design yielded four groups with two levels of current dysphoria status (yes/no) and history of depression (yes/no), enabling comparisons of relative risk. Each participant completed two visual oddball tasks. In the experimental task, participants responded or inhibited a response to infrequently presented sad or happy target faces in the context of frequently presented neutral faces. In the non-affective control task, participants responded only to faces that fit into one of three broad age groupings. Behavioral (e.g., reaction times, response errors), psychophysiological (ERP components), and self-report (e.g., rumination) measures relevant to selective attention and inhibition were analyzed. Between- and within-groups contrasts were conducted to reveal whether at-risk groups exhibit attentional bias and inhibitory deficiency specific to depressive information. Also, the study examined whether different operationalizations of depression risk evince common or distinct mechanisms of vulnerability. Across the full sample, previous depression was associated with greater P3b amplitude for sad target faces than happy target faces, in contrast with the depression naïve group. However in males, only the combination of previous depression and current dysphoria were linked to elevated P3s following sad targets. Evidence for a sad affect inhibition deficit was limited to dysphoric females' increased errors of commission following sad distracter faces. Results suggest that specific operationalizations of risk may be characterized by an attentional bias toward depressive facial affect in the social environment, which could promote additional depressogenic cognition and social behavior. Theoretical ramifications regarding gender and state versus trait vulnerability are also discussed

Training methods for facial image comparison: a literature review

This literature review was commissioned to explore the psychological literature relating to facial image comparison with a particular emphasis on whether individuals can be trained to improve performance on this task. Surprisingly few studies have addressed this question directly. As a consequence, this review has been extended to cover training of face recognition and training of different kinds of perceptual comparisons where we are of the opinion that the methodologies or findings of such studies are informative. The majority of studies of face processing have examined face recognition, which relies heavily on memory. This may be memory for a face that was learned recently (e.g. minutes or hours previously) or for a face learned longer ago, perhaps after many exposures (e.g. friends, family members, celebrities). Successful face recognition, irrespective of the type of face, relies on the ability to retrieve the to-berecognised face from long-term memory. This memory is then compared to the physically present image to reach a recognition decision. In contrast, in face matching task two physical representations of a face (live, photographs, movies) are compared and so long-term memory is not involved. Because the comparison is between two present stimuli rather than between a present stimulus and a memory, one might expect that face matching, even if not an easy task, would be easier to do and easier to learn than face recognition. In support of this, there is evidence that judgment tasks where a presented stimulus must be judged by a remembered standard are generally more cognitively demanding than judgments that require comparing two presented stimuli Davies & Parasuraman, 1982; Parasuraman & Davies, 1977; Warm and Dember, 1998). Is there enough overlap between face recognition and matching that it is useful to look at the literature recognition? No study has directly compared face recognition and face matching, so we turn to research in which people decided whether two non-face stimuli were the same or different. In these studies, accuracy of comparison is not always better when the comparator is present than when it is remembered. Further, all perceptual factors that were found to affect comparisons of simultaneously presented objects also affected comparisons of successively presented objects in qualitatively the same way. Those studies involved judgments about colour (Newhall, Burnham & Clark, 1957; Romero, Hita & Del Barco, 1986), and shape (Larsen, McIlhagga & Bundesen, 1999; Lawson, Bülthoff & Dumbell, 2003; Quinlan, 1995). Although one must be cautious in generalising from studies of object processing to studies of face processing (see, e.g., section comparing face processing to object processing), from these kinds of studies there is no evidence to suggest that there are qualitative differences in the perceptual aspects of how recognition and matching are done. As a result, this review will include studies of face recognition skill as well as face matching skill. The distinction between face recognition involving memory and face matching not involving memory is clouded in many recognition studies which require observers to decide which of many presented faces matches a remembered face (e.g., eyewitness studies). And of course there are other forensic face-matching tasks that will require comparison to both presented and remembered comparators (e.g., deciding whether any person in a video showing a crowd is the target person). For this reason, too, we choose to include studies of face recognition as well as face matching in our revie