Steady state visually evoked potential correlates of static and dynamic emotional face processing

While the neural regions associated with facial identity recognition are considered to be well defined, the neural correlates of non-moving and moving images of facial emotion processing are less clear. This study examined the brain electrical activity changes in 26 participants (14 males M = 21.64, SD = 3.99; 12 females M = 24.42, SD = 4.36), during a passive face viewing task, a scrambled face task and separate emotion and gender face discrimination tasks. The steady state visual evoked potential (SSVEP) was recorded from 64-electrode sites. Consistent with previous research, face related activity was evidenced at scalp regions over the parieto-temporal region approximately 170 ms after stimulus presentation. Results also identified different SSVEP spatio-temporal changes associated with the processing of static and dynamic facial emotions with respect to gender, with static stimuli predominately associated with an increase in inhibitory processing within the frontal region. Dynamic facial emotions were associated with changes in SSVEP response within the temporal region, which are proposed to index inhibitory processing. It is suggested that static images represent non-canonical stimuli which are processed via different mechanisms to their more ecologically valid dynamic counterparts.

Facial emotion and identity processing development in 5- to 15-year-old children

Most developmental studies of emotional face processing to date have focused on infants and very young children. Additionally, studies that examine emotional face processing in older children do not distinguish development in emotion and identity face processing from more generic age-related cognitive improvement. In this study, we developed a paradigm that measures processing of facial expression in comparison to facial identity and complex visual stimuli. The three matching tasks were developed (i.e., facial emotion matching, facial identity matching, and butterfly wing matching) to include stimuli of similar level of discriminability and to be equated for task difficulty in earlier samples of young adults. Ninety-two children aged 5–15 years and a new group of 24 young adults completed these three matching tasks. Young children were highly adept at the butterfly wing task relative to their performance on both face-related tasks. More importantly, in older children, development of facial emotion discrimination ability lagged behind that of facial identity discrimination.

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.

A new approach to teaching signal processing at undergraduate level

This paper describes the design and implementation of a unique undergraduate program in signal processing at the Queensland University of Technology (QUT). The criteria that influenced the choice of the subjects and the laboratories developed to support them are presented. A recently established Signal Processing Research Centre (SPRC) has played an important role in the development of the signal processing teaching program. The SPRC also provides training opportunities for postgraduate studies and research.

The development of a new signal processing program at the Queensland University of Technology

The School of Electrical and Electronic Systems Engineering at Queensland University of Technology, Brisbane, Australia (QUT), offers three bachelor degree courses in electrical and computer engineering. In all its courses there is a strong emphasis on signal processing. A newly established Signal Processing Research Centre (SPRC) has played an important role in the development of the signal processing units in these courses. This paper describes the unique design of the undergraduate program in signal processing at QUT, the laboratories developed to support it, and the criteria that influenced the design.

Academic strategy planning for a university research centre

The Signal Processing Research Centre (SPRC) at QUT recently formulated an academic strategy plan. This paper describes the various factors that must be considered in undertaking such a planning process. It also illustrates the need for a university research centre to plan for its teaching activities as well as its research activities. Complementary teaching and research are essential to the achievement of the strategic objectives of a university centre.

MEG Adaptation resolves the spatiotemporal characteristics of face-sensitive brain responses

An unresolved goal in face perception is to identify brain areas involved in face processing and simultaneously understand the timing of their involvement. Currently, high spatial resolution imaging techniques identify the fusiform gyrus as subserving processing of invariant face features relating to identity. High temporal resolution imaging techniques localize an early latency evoked component—the N/M170—as having a major generator in the fusiform region; however, this evoked component is not believed to be associated with the processing of identity. To resolve this, we used novel magnetoencephalographic beamformer analyses to localize cortical regions in humans spatially with trial-by-trial activity that differentiated faces and objects and to interrogate their functional sensitivity by analyzing the effects of stimulus repetition. This demonstrated a temporal sequence of processing that provides category-level and then item-level invariance. The right fusiform gyrus showed adaptation to faces (not objects) at ∼150 ms after stimulus onset regardless of face identity; however, at the later latency of ∼200–300 ms, this area showed greater adaptation to repeated identity faces than to novel identities. This is consistent with an involvement of the fusiform region in both early and midlatency face-processing operations, with only the latter showing sensitivity to invariant face features relating to identity.

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.

Quality based frame selection for video face recognition

Quality based frame selection is a crucial task in video face recognition, to both improve the recognition rate and to reduce the computational cost. In this paper we present a framework that uses a variety of cues (face symmetry, sharpness, contrast, closeness of mouth, brightness and openness of the eye) to select the highest quality facial images available in a video sequence for recognition. Normalized feature scores are fused using a neural network and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face recognition system. Experiments on the Honda/UCSD database shows that the proposed method selects the best quality face images in the video sequence, resulting in improved recognition performance.

Deformable face ensemble alignment with robust grouped-L1 anchors

Many methods exist at the moment for deformable face fitting. A drawback to nearly all these approaches is that they are (i) noisy in terms of landmark positions, and (ii) the noise is biased across frames (i.e. the misalignment is toward common directions across all frames). In this paper we propose a grouped $\mathcal{L}1$-norm anchored method for simultaneously aligning an ensemble of deformable face images stemming from the same subject, given noisy heterogeneous landmark estimates. Impressive alignment performance improvement and refinement is obtained using very weak initialization as "anchors".

Digital social signal processing - theorectical underpinning and research agenda

Organizations make increasingly use of social media in order to compete for customer awareness and improve the quality of their goods and services. Multiple techniques of social media analysis are already in use. Nevertheless, theoretical underpinnings and a sound research agenda are still unavailable in this field at the present time. In order to contribute to setting up such an agenda, we introduce digital social signal processing (DSSP) as a new research stream in IS that requires multi-facetted investigations. Our DSSP concept is founded upon a set of four sequential activities: sensing digital social signals that are emitted by individuals on social media; decoding online data of social media in order to reconstruct digital social signals; matching the signals with consumers’ life events; and configuring individualized goods and service offerings tailored to the individual needs of customers. We further contribute to tying loose ends of different research areas together, in order to frame DSSP as a field for further investigation. We conclude with developing a research agenda.

Liveness detection based on 3D face shape analysis

In recent years face recognition systems have been applied in various useful applications, such as surveillance, access control, criminal investigations, law enforcement, and others. However face biometric systems can be highly vulnerable to spoofing attacks where an impostor tries to bypass the face recognition system using a photo or video sequence. In this paper a novel liveness detection method, based on the 3D structure of the face, is proposed. Processing the 3D curvature of the acquired data, the proposed approach allows a biometric system to distinguish a real face from a photo, increasing the overall performance of the system and reducing its vulnerability. In order to test the real capability of the methodology a 3D face database has been collected simulating spoofing attacks, therefore using photographs instead of real faces. The experimental results show the effectiveness of the proposed approach.

Quality based frame selection for face clustering in news video

Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.

Techniques to effectively buffer schedules in the face of uncertainties

Resource assignment and scheduling is a difficult task when job processing times are stochastic, and resources are to be used for both known and unknown demand. To operate effectively within such an environment, several novel strategies are investigated. The first focuses upon the creation of a robust schedule, and utilises the concept of strategically placed idle time (i.e. buffering). The second approach introduces the idea of maintaining a number of free resources at each time, and culminates in another form of strategically placed buffering. The attraction of these approaches is that they are easy to grasp conceptually, and mimic what practitioners already do in practice. Our extensive numerical testing has shown that these techniques ensure more prompt job processing, and reduced job cancellations and waiting time. They are effective in the considered setting and could easily be adapted for many real life problems, for instance those in health care. This article has more importantly demonstrated that integrating the two approaches is a better strategy and will provide an effective stochastic scheduling approach.

“It puts a human face on the researched”: A qualitative evaluation of an Indigenous research governance model

Objective This study aimed to describe the Inala Aboriginal and Torres Strait Islander Community Jury for Health Research, and evaluate its usefulness as a model of Indigenous research governance within an urban Indigenous primary health care service from the perspectives of Jury members and researchers. Methods Informed by a phenomenological approach and using narrative inquiry, a focus group was conducted with Jury members and key informant interviews were undertaken with researchers who had presented to the Community Jury in its first year of operation. Results The Jury was a site of identity work for researchers and Jury members, providing an opportunity to observe and affirm community cultural protocols. Although researchers and Jury members had differing levels of research literacy, the Jury processes enabled respectful communication and relationships to form which positively influenced research practice, community aspirations and clinical care. Discussion The Jury processes facilitated transformative research practice among researchers, and resulted in transference of power from researchers to the Jury members to the mutual benefit of both. Conclusion Ethical Indigenous health research practice requires an engagement with Indigenous peoples and knowledges at the research governance level, not simply as subjects or objects of research.