On the application of the probabilistic linear discriminant analysis to face recognition across expression

Facial expression is one of the main issues of face recognition in uncontrolled environments. In this paper, we apply the probabilistic linear discriminant analysis (PLDA) method to recognize faces across expressions. Several PLDA approaches are tested and cross-evaluated on the Cohn-Kanade and JAFFE databases. With less samples per gallery subject, high recognition rates comparable to previous works have been achieved indicating the robustness of the approaches. Among the approaches, the mixture of PLDAs has demonstrated better performances. The experimental results also indicate that facial regions around the cheeks, eyes, and eyebrows are more discriminative than regions around the mouth, jaw, chin, and nose.

How Does Information Processing Speed Relate to the Attentional Blink?

Background When observers are asked to identify two targets in rapid sequence, they often suffer profound performance deficits for the second target, even when the spatial location of the targets is known. This attentional blink (AB) is usually attributed to the time required to process a previous target, implying that a link should exist between individual differences in information processing speed and the AB. Methodology/Principal Findings The present work investigated this question by examining the relationship between a rapid automatized naming task typically used to assess information-processing speed and the magnitude of the AB. The results indicated that faster processing actually resulted in a greater AB, but only when targets were presented amongst high similarity distractors. When target-distractor similarity was minimal, processing speed was unrelated to the AB. Conclusions/Significance Our findings indicate that information-processing speed is unrelated to target processing efficiency per se, but rather to individual differences in observers' ability to suppress distractors. This is consistent with evidence that individuals who are able to avoid distraction are more efficient at deploying temporal attention, but argues against a direct link between general processing speed and efficient information selection.

Why the long face?

In this video, a male voice recites a script comprised entirely of jokes. Words flash on screen in time with the spoken words. Sometimes the two sets of words match, and sometimes they differ. This work examines processes of signification. It emphasizes disruption and disconnection as fundamental and generative operations in making meaning. Extending on post-structural and deconstructionist ideas, this work questions the relationship between written and spoken words. By deliberately confusing the signifying structures of jokes and narratives, it questions the sites and mechanisms of comprehension, humour and signification.

Individual differences in drivers’ cognitive processing of road safety messages

Using Gray and McNaughton’s (2000) revised Reinforcement Sensitivity Theory (r-RST), we examined the influence of personality on processing of words presented in gain-framed and loss-framed anti-speeding messages and how the processing biases associated with personality influenced message acceptance. The r-RST predicts that the nervous system regulates personality and that behaviour is dependent upon the activation of the Behavioural Activation System (BAS), activated by reward cues and the Fight-Flight-Freeze System (FFFS), activated by punishment cues. According to r-RST, individuals differ in the sensitivities of their BAS and FFFS (i.e., weak to strong), which in turn leads to stable patterns of behaviour in the presence of rewards and punishments, respectively. It was hypothesised that individual differences in personality (i.e., strength of the BAS and the FFFS) would influence the degree of both message processing (as measured by reaction time to previously viewed message words) and message acceptance (measured three ways by perceived message effectiveness, behavioural intentions, and attitudes). Specifically, it was anticipated that, individuals with a stronger BAS would process the words presented in the gain-frame messages faster than those with a weaker BAS and individuals with a stronger FFFS would process the words presented in the loss-frame messages faster than those with a weaker FFFS. Further, it was expected that greater processing (faster reaction times) would be associated with greater acceptance for that message. Driver licence holding students (N = 108) were recruited to view one of four anti-speeding messages (i.e., social gain-frame, social loss-frame, physical gain-frame, and physical loss-frame). A computerised lexical decision task assessed participants’ subsequent reaction times to message words, as an indicator of the extent of processing of the previously viewed message. Self-report measures assessed personality and the three message acceptance measures. As predicted, the degree of initial processing of the content of the social gain-framed message mediated the relationship between the reward sensitive trait and message effectiveness. Initial processing of the physical loss-framed message partially mediated the relationship between the punishment sensitive trait and both message effectiveness and behavioural intention ratings. These results show that reward sensitivity and punishment sensitivity traits influence cognitive processing of gain-framed and loss-framed message content, respectively, and subsequently, message effectiveness and behavioural intention ratings. Specifically, a range of road safety messages (i.e., gain-frame and loss-frame messages) could be designed which align with the processing biases associated with personality and which would target those individuals who are sensitive to rewards and those who are sensitive to punishments.

Evaluation of image resolution and super-resolution on face recognition performance

While researchers strive to improve automatic face recognition performance, the relationship between image resolution and face recognition performance has not received much attention. This relationship is examined systematically and a framework is developed such that results from super-resolution techniques can be compared. Three super-resolution techniques are compared with the Eigenface and Elastic Bunch Graph Matching face recognition engines. Parameter ranges over which these techniques provide better recognition performance than interpolated images is determined.

Life in the internet economy and the changing face of property use

Increased participation in the internet economy is actively encouraged and supported by all levels of government. Research to date clearly shows the positive impacts that increased internet access can bring, particularly for rural Australia. Meanwhile, for the most part, identification of any negative impacts of increased broadband access on existing and potential property uses is avoided. The aim of this article is to identify issues for property use arising as a consequence of increased engagement in the internet economy. The article commences by clarifying what is meant by the term ‘internet economy’ before highlighting current impacts of the internet. It concludes by suggesting potential impacts for property and property uses in the future.

In the pursuit of effective affective computing : the relationship between features and registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.

Engaging undergraduate nursing students in face-to-face tutorials

Chronic nursing shortages have placed increasing pressure on many nursing schools to recruit greater numbers of students with the consequence of larger class sizes. Larger class sizes have the potential to lead to student disengagement. This paper describes a case study that examined the strategies used by a group of nursing lecturers to engage students and to overcome passivity in a Bachelor of Nursing programme. A non-participant observer attended 20 tutorials to observe five academics deliver four tutorials each. Academics were interviewed both individually and as a group following the completion of all tutorial observations. All observations, field notes, interviews and focus groups were coded separately and major themes identified. From this analysis two broad categories emerged: getting students involved; and engagement as a struggle. Academics used a wide variety of techniques to interest and involve students. Additionally, academics desired an equal relationship with students. They believed that both they and the students had some power to influence the dynamics of tutorials and that neither party had ultimate power. The findings of this study serve to re-emphasise past literature which suggests that to engage students, the academics must also engage.

The acquisition of an artificial logographic script and bilingual working memory : Evidence for L1-specific orthographic processing skills transfer in Chinese-English bilinguals

Studies of orthographic skills transfer between languages focus mostly on working memory (WM) ability in alphabetic first language (L1) speakers when learning another, often alphabetically congruent, language. We report two studies that, instead, explored the transferability of L1 orthographic processing skills in WM in logographic-L1 and alphabetic-L1 speakers. English-French bilingual and English monolingual (alphabetic-L1) speakers, and Chinese-English (logographic-L1) speakers, learned a set of artificial logographs and associated meanings (Study 1). The logographs were used in WM tasks with and without concurrent articulatory or visuo-spatial suppression. The logographic-L1 bilinguals were markedly less affected by articulatory suppression than alphabetic-L1 monolinguals (who did not differ from their bilingual peers). Bilinguals overall were less affected by spatial interference, reflecting superior phonological processing skills or, conceivably, greater executive control. A comparison of span sizes for meaningful and meaningless logographs (Study 2) replicated these findings. However, the logographic-L1 bilinguals’ spans in L1 were measurably greater than those of their alphabetic-L1 (bilingual and monolingual) peers; a finding unaccounted for by faster articulation rates or differences in general intelligence. The overall pattern of results suggests an advantage (possibly perceptual) for logographic-L1 speakers, over and above the bilingual advantage also seen elsewhere in third language (L3) acquisition.

Multiple cameras for audio-visual speech recognition in an automotive environment

Audio-visualspeechrecognition, or the combination of visual lip-reading with traditional acoustic speechrecognition, has been previously shown to provide a considerable improvement over acoustic-only approaches in noisy environments, such as that present in an automotive cabin. The research presented in this paper will extend upon the established audio-visualspeechrecognition literature to show that further improvements in speechrecognition accuracy can be obtained when multiple frontal or near-frontal views of a speaker's face are available. A series of visualspeechrecognition experiments using a four-stream visual synchronous hidden Markov model (SHMM) are conducted on the four-camera AVICAR automotiveaudio-visualspeech database. We study the relative contribution between the side and central orientated cameras in improving visualspeechrecognition accuracy. Finally combination of the four visual streams with a single audio stream in a five-stream SHMM demonstrates a relative improvement of over 56% in word recognition accuracy when compared to the acoustic-only approach in the noisiest conditions of the AVICAR database.

A tensor encoding model for semantic processing

This paper develops and evaluates an enhanced corpus based approach for semantic processing. Corpus based models that build representations of words directly from text do not require pre-existing linguistic knowledge, and have demonstrated psychologically relevant performance on a number of cognitive tasks. However, they have been criticised in the past for not incorporating sufficient structural information. Using ideas underpinning recent attempts to overcome this weakness, we develop an enhanced tensor encoding model to build representations of word meaning for semantic processing. Our enhanced model demonstrates superior performance when compared to a robust baseline model on a number of semantic processing tasks.

Nonprofit organisations face a restructuring state : the case of local social services in the Hunter region of New South Wales

This paper is concerned with certain of the characteristics of local social services, and their role in a restructuring Australian welfare state. I am particularly concerned with the distinctive gender characteristics of these organisations, because in comparison with most other organisations they have a feminised quality. This partly mirrors women's traditional role of undertaking the major part of the caring labour of society. However, simultaneously work in these organisation deviates from more traditional patterns where employed women occupy subordinate positions. In many community organisations, women occupy leadership roles. The analysis here is concerned with the apparently paradoxical nature of these organisations in their capacity to entrench traditional gender roles and to challenge these by allowing women to fill management positions. It is also concerned to examine whether changes that have been occurring in the community services sector over the last two decades are likely to enhance women's general position in the society, or diminish the power exercised by women. The paper draws in a preliminary way on a study of local services in the Hunter Region of NSW undertaken in the latter half of 1992. These preliminary findings are set against the broader picture of developments in the contemporary welfare state.