Facial identity and facial expression matching in 5 - 12-year-old children and adults

Facial identity and facial expression matching tasks were completed by 5–12-year-old children and adults using stimuli extracted from the same set of normalized faces. Configural and feature processing were examined using speed and accuracy of responding and facial feature selection, respectively. Facial identity matching was slower than face expression matching for all age groups. Large age effects were found on both speed and accuracy of responding and feature use in both identity and expression matching tasks. Eye region preference was found on the facial identity task and mouth region preference on the facial expression task. Use of mouth region information for facial expression matching increased with age, whereas use of eye region information for facial identity matching peaked early. The feature use information suggests that the specific use of primary facial features to arrive at identity and emotion matching judgments matures across middle childhood.

Mirror neuron activation is associated with facial emotion processing

Theoretical accounts suggest that mirror neurons play a crucial role in social cognition. The current study used transcranial-magnetic stimulation (TMS) to investigate the association between mirror neuron activation and facialemotion processing, a fundamental aspect of social cognition, among healthy adults (n = 20). Facial emotion processing of static (but not dynamic) images correlated significantly with an enhanced motor response, proposed to reflect mirror neuron activation. These correlations did not appear to reflect general facial processing or pattern recognition, and provide support to current theoretical accounts linking the mirror neuron system to aspects of social cognition. We discuss the mechanism by which mirror neurons might facilitate facial emotion recognition.

Facial emotion processing in schizophrenia : no evidence for a deficit specific to negative emotions in a differential deficit design

People with schizophrenia perform poorly when recognising facial expressions of emotion, particularly negative emotions such as fear. This finding has been taken as evidence of a “negative emotion specific deficit”, putatively associated with a dysfunction in the limbic system, particularly the amygdala. An alternative explanation is that greater difficulty in recognising negative emotions may reflect a priori differences in task difficulty. The present study uses a differential deficit design to test the above argument. Facial emotion recognition accuracy for seven emotion categories was compared across three groups. Eighteen schizophrenia patients and one group of healthy age- and gender-matched controls viewed identical sets of stimuli. A second group of 18 age- and gender-matched controls viewed a degraded version of the same stimuli. The level of stimulus degradation was chosen so as to equate overall level of accuracy to the schizophrenia patients. Both the schizophrenia group and the degraded image control group showed reduced overall recognition accuracy and reduced recognition accuracy for fearful and sad facial stimuli compared with the intact-image control group. There were no differences in recognition accuracy for any emotion category between the schizophrenia group and the degraded image control group. These findings argue against a negative emotion specific deficit in schizophrenia.

Functional MRI of facial emotion recognition deficits in schizophrenia and their electrophysiological correlates

Empirical evidence suggests impaired facial emotion recognition in schizophrenia. However, the nature of this deficit is the subject of ongoing research. The current study tested the hypothesis that a generalized deficit at an early stage of face-specific processing (i.e. putatively subserved by the fusiform gyrus) accounts for impaired facial emotion recognition in schizophrenia as opposed to the Negative Emotion-specific Deficit Model, which suggests impaired facial information processing at subsequent stages. Event-related potentials (ERPs) were recorded from 11 schizophrenia patients and 15 matched controls while performing a gender discrimination and a facial emotion recognition task. Significant reduction of the face-specific vertex positive potential (VPP) at a peak latency of 165 ms was confirmed in schizophrenia subjects whereas their early visual processing, as indexed by P1, was found to be intact. Attenuated VPP was found to correlate with subsequent P3 amplitude reduction and to predict accuracy when performing a facial emotion discrimination task. A subset of ten schizophrenia patients and ten matched healthy control subjects also performed similar tasks in the magnetic resonance imaging scanner. Patients showed reduced blood oxygenation level-dependent (BOLD) activation in the fusiform, inferior frontal, middle temporal and middle occipital gyrus as well as in the amygdala. Correlation analyses revealed that VPP and the subsequent P3a ERP components predict fusiform gyrus BOLD activation. These results suggest that problems in facial affect recognition in schizophrenia may represent flow-on effects of a generalized deficit in early visual processing.

Differential susceptibility to performance degradation across categories of facial emotion - a model confirmation

Patients with a number of psychiatric and neuropathological conditions demonstrate problems in recognising facial expressions of emotion. Research indicating that patients with schizophrenia perform more poorly in the recognition of negative valence facial stimuli than positive valence stimuli has been interpreted as evidence of a negative emotion specific deficit. An alternate explanation rests in the psychometric properties of the stimulus materials. This model suggests that the pattern of impairment observed in schizophrenia may reflect initial discrepancies in task difficulty between stimulus categories, which are not apparent in healthy subjects because of ceiling effects. This hypothesis is tested, by examining the performance of healthy subjects in a facial emotion categorisation task with three levels of stimulus resolution. Results confirm the predictions of the model, showing that performance degrades differentially across emotion categories, with the greatest deterioration to negative valence stimuli. In the light of these results, a possible methodology for detecting emotion specific deficits in clinical samples is discussed.

FaceXpress : an integrated software suite for facial emotion stimulus manipulation and facial measurement

The characterisation of facial expression through landmark-based analysis methods such as FACEM (Pilowsky & Katsikitis, 1994) has a variety of uses in psychiatric and psychological research. In these systems, important structural relationships are extracted from images of facial expressions by the analysis of a pre-defined set of feature points. These relationship measures may then be used, for instance, to assess the degree of variability and similarity between different facial expressions of emotion. FaceXpress is a multimedia software suite that provides a generalised workbench for landmark-based facial emotion analysis and stimulus manipulation. It is a flexible tool that is designed to be specialised at runtime by the user. While FaceXpress has been used to implement the FACEM process, it can also be configured to support any other similar, arbitrary system for quantifying human facial emotion. FaceXpress also implements an integrated set of image processing tools and specialised tools for facial expression stimulus production including facial morphing routines and the generation of expression-representative line drawings from photographs.

A generalised deficit can account for problems in facial emotion recognition in schizophrenia

Neuroimaging research has shown localised brain activation to different facial expressions. This, along with the finding that schizophrenia patients perform poorly in their recognition of negative emotions, has raised the suggestion that patients display an emotion specific impairment. We propose that this asymmetry in performance reflects task difficulty gradations, rather than aberrant processing in neural pathways subserving recognition of specific emotions. A neural network model is presented, which classifies facial expressions on the basis of measurements derived from human faces. After training, the network showed an accuracy pattern closely resembling that of healthy subjects. Lesioning of the network led to an overall decrease in the network’s discriminant capacity, with the greatest accuracy decrease to fear, disgust and anger stimuli. This implies that the differential pattern of impairment in schizophrenia patients can be explained without having to postulate impairment of specific processing modules for negative emotion recognition.

Using viewer’s facial expression and heart rate for sports video highlights detection

Viewer interests, evoked by video content, can potentially identify the highlights of the video. This paper explores the use of facial expressions (FE) and heart rate (HR) of viewers captured using camera and non-strapped sensor for identifying interesting video segments. The data from ten subjects with three videos showed that these signals are viewer dependent and not synchronized with the video contents. To address this issue, new algorithms are proposed to effectively combine FE and HR signals for identifying the time when viewer interest is potentially high. The results show that, compared with subjective annotation and match report highlights, ‘non-neutral’ FE and ‘relatively higher and faster’ HR is able to capture 60%-80% of goal, foul, and shot-on-goal soccer video events. FE is found to be more indicative than HR of viewer’s interests, but the fusion of these two modalities outperforms each of them.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

Made by motion: A conceptual framework for abstracted animation derived from motion-captured movements

Despite an increasing number of acclaimed abstract animations being created through the application of motion capture technologies there has been little detailed documentation and analysis of this approach for abstract animation production. More specifically, it is unclear what the key considerations are, and what issues practitioners might face, when integrating motion capture movement data into their practice. In response to this issue this study explored and documented the practice of generating abstract visual and temporal artefacts from motion captured dance movements that compose abstract animated short films. The study has resulted in a possible framework for this form of practice and outlines five key considerations which should be taken into account by practitioners who use motion capture in the production of abstract animated short films.

A genome-wide association study identifies five loci influencing facial morphology in Europeans

Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes-PRDM16, PAX3, TP63, C5orf50, and COL17A1-in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

The use of animation to promote student learning about the importance of mental well-being for tertiary study success

It is now widely acknowledged that student mental well-being is a critical factor in the tertiary student learning experience and is important to student learning success. The issue of student mental well-being also has implications for effective student transition out of university and into the world of work. It is therefore vital that intentional strategies are adopted by universities both within the formal curriculum, and outside it, to promote student well-being and to work proactively and preventatively to avoid a decline in student psychological well-being. This paper describes how the Queensland University of Technology Law School is using animation to teach students about the importance for their learning success of the protection of their mental well-being. Mayer and Moreno (2002) define an animation as an external representation with three main characteristics: (1) it is a pictorial representation, (2) it depicts apparent movement, and (3) it consists of objects that are artificially created through drawing or some other modelling technique. Research into the effectiveness of animation as a tool for tertiary student learning engagement is relatively new and growing field of enquiry. Nash argues, for example, that animations provide a “rich, immersive environment [that] encourages action and interactivity, which overcome an often dehumanizing learning management system approach” (Nash, 2009, 25). Nicholas states that contemporary millennial students in universities today, have been immersed in animated multimedia since their birth and in fact need multimedia to learn and communicate effectively (2008). However, it has also been established, for example through the work of Lowe (2003, 2004, 2008) that animations can place additional perceptual, attentional, and cognitive demands on students that they are not always equipped to cope with. There are many different genres of animation. The dominant style of animation used in the university learning environment is expository animation. This approach is a useful tool for visualising dynamic processes and is used to support student understanding of subjects and themes that might otherwise be perceived as theoretically difficult and disengaging. It is also a form of animation that can be constructed to avoid any potential negative impact on cognitive load that the animated genre might have. However, the nature of expository animation has limitations for engaging students, and can present as clinical and static. For this reason, the project applied Kombartzky, Ploetzner, Schlag, and Metz’s (2010) cognitive strategy for effective student learning from expository animation, and developed a hybrid form of animation that takes advantage of the best elements of expository animation techniques along with more engaging short narrative techniques. First, the paper examines the existing literature on the use of animation in tertiary educational contexts. Second, the paper describes how animation was used at QUT Law School to teach students about the issue of mental well-being and its importance to their learning success. Finally, the paper analyses the potential of the use of animation, and of the cognitive strategy and animation approach trialled in the project, as a teaching tool for the promotion of student learning about the importance of mental well-being.

A flexible hierarchical approach for facial age estimation based on multiple features

Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

Apprehending the void: Using animation to interpret the genius loci of the Peel Island Lazaret

This practice-led research project harnesses the plasmatic nature of animation (Eisenstein 1989) to embody the in-between state of being of the Peel Island Lazaret on the island of Teerk Roo Ra in Moreton Bay, Queensland. In this project the genius loci of this place is expressed through the development of a series of creative works that employs the unique transformative quality of animation to push and pull at the boundary lines between what can be apprehended as the ‘real’ and the ‘imaginary’. Drawing on the physical approach of Czech surrealist animator Jan Švankmajer and cultural theories from Australian writer Ross Gibson, this study re-members and re-imagines the site of the Lazaret as a liminal, uncanny place. This study investigates how conceptions of place are overlaid by aspects of history, memory and the imagination and these discoveries contribute to the currently limited academic discourse around place and place-making in animation practice in Australia.