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".

Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

The magic of numbers and the amazing disappearing act : the politics of counting youth homelessness

No-one wants to see young people who are no longer able to stay at home with their parents living in situations that are neither stable nor safe. Most Australians also appreciate that youth homelessness is typically a result of factors beyond the control of young people like poverty, lack of affordable housing, parental divorce or separation, family conflict and violence, sexual abuse, or mental health problems.1 Since the Burdekin Report of 1989 first put the issue on the national agenda, youth homelessness has been a point of some political sensitivity as the numbers of young homeless stayed stubbornly high through the 1990s and into the 2000s.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Cohort normalization based sparse representation for undersampled face recognition

Abstract. In recent years, sparse representation based classification(SRC) has received much attention in face recognition with multipletraining samples of each subject. However, it cannot be easily applied toa recognition task with insufficient training samples under uncontrolledenvironments. On the other hand, cohort normalization, as a way of mea-suring the degradation effect under challenging environments in relationto a pool of cohort samples, has been widely used in the area of biometricauthentication. In this paper, for the first time, we introduce cohort nor-malization to SRC-based face recognition with insufficient training sam-ples. Specifically, a user-specific cohort set is selected to normalize theraw residual, which is obtained from comparing the test sample with itssparse representations corresponding to the gallery subject, using poly-nomial regression. Experimental results on AR and FERET databases show that cohort normalization can bring SRC much robustness against various forms of degradation factors for undersampled face recognition.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.

Grunt language versus accent : the perceived communication barriers between international medical graduates and patients in Central Wheatbelt catchments

Due to the chronic shortages of GPs in Australian rural and remote regions, considerable numbers of international medical graduates (IMG) have been recruited. IMG experience many difficulties when relocating to Australia with one of the most significant being effective GP-patient communication. Given that this is essential for effective consultation it can have a substantial impact on health care. A purposive sample of seven practising GPs (five IMG, two Australian-trained doctors (ATD)) was interviewed using a semistructured face-to-face interviewing technique. GPs from Nigeria, Egypt, United Kingdom, India, Singapore and Australia participated. Interviews were transcribed and then coded. The authors used qualitative thematic analysis of interview transcripts to identify common themes. IMG-patient communication barriers were considered significant in the Wheatbelt region as identified by both IMG and ATD. ATD indicated they were aware of IMG-patient communication issues resulting in subsequent consults with patients to explain results and diagnoses. Significantly, a lack of communication between ATD and IMG also emerged, creating a further barrier to effective communication. Analysis of the data generated several important findings that rural GP networks should consider when integrating new IMG into the community. Addressing the challenges related to cross-cultural differences should be a priority, in order to enable effective communication. More open communication between ATD and IMG about GP-patient communication barriers and education programs around GP-patient communication would help both GP and patient satisfaction.

Standing brave in the face of rapid curriculum change : EAL/D teachers speak about critical literacy and its place in senior English teaching

Critical literacy (CL) has been the subject of much debate in the Australian public and education arenas since 2002. Recently, this debate has dissipated as literacy education agendas and attendant policies shift to embrace more hybrid models and approaches to the teaching of senior English. This paper/presentation reports on the views expressed by four teachers of senior English about critical literacy and it’s relevance to students who are from culturally and linguistically diverse backgrounds who are learning English while undertaking senior studies in high school. Teachers’ understandings of critical literacy are important, esp. given the emphasis on Critical and Creative Thinking and Literacy as two of the General Capabilities underpinning the Australian national curriculum. Using critical discourse analysis, data from four specialist ESL teachers in two different schools were analysed for the ways in which these teachers construct critical literacy. While all four teachers indicated significant commitment to critical literacy as an approach to English language teaching, the understandings they articulated varied from providing forms of access to powerful genres, to rationalist approaches to interrogating text, to a type of ‘critical-aesthetic’ analysis of text construction. Implications are also discussed.

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.

Effect of Reynolds numbers on flow past four square cylinders in an in-line square configuration for different gap spacings

In this paper two-dimensional (2-D) numerical investigation of flow past four square cylinders in an in-line square configuration are performed using the lattice Boltzmann method. The gap spacing g=s/d is set at 1, 3 and 6 and Reynolds number ranging from Re=60 to 175. We observed four distinct wake patterns: (i) a steady wake pattern (Re=60 and g=1) (ii) a stable shielding wake pattern (80≤Re≤175 and g=1) (iii) a wiggling shielding wake pattern (60≤Re≤175 and g=3) (iv) a vortex shedding wake pattern (60≤Re≤175 and g=6) At g=1, the Reynolds number is observed to have a strong effect on the wake patterns. It is also found that at g=1, the secondary cylinder interaction frequency significantly contributes for drag and lift coefficients signal. It is found that the primary vortex shedding frequency dominates the flow and the role of secondary cylinder interaction frequency almost vanish at g=6. It is observed that the jet between the gaps strongly influenced the wake interaction for different gap spacing and Reynolds number combination. To fully understand the wake transformations the details vorticity contour visualization, power spectra of lift coefficient signal and time signal analysis of drag and lift coefficients also presented in this paper.

Visual front-end wars : Viola-Jones face detector vs Fourier Lucas-Kanade

The performance of visual speech recognition (VSR) systems are significantly influenced by the accuracy of the visual front-end. The current state-of-the-art VSR systems use off-the-shelf face detectors such as Viola- Jones (VJ) which has limited reliability for changes in illumination and head poses. For a VSR system to perform well under these conditions, an accurate visual front end is required. This is an important problem to be solved in many practical implementations of audio visual speech recognition systems, for example in automotive environments for an efficient human-vehicle computer interface. In this paper, we re-examine the current state-of-the-art VSR by comparing off-the-shelf face detectors with the recently developed Fourier Lucas-Kanade (FLK) image alignment technique. A variety of image alignment and visual speech recognition experiments are performed on a clean dataset as well as with a challenging automotive audio-visual speech dataset. Our results indicate that the FLK image alignment technique can significantly outperform off-the shelf face detectors, but requires frequent fine-tuning.

Human identification at a distance using iris and face

This research has successfully applied super-resolution and multiple modality fusion techniques to address the major challenges of human identification at a distance using face and iris. The outcome of the research is useful for security applications.

I’m friends with Louie the Fly, not Mortein : Conceptualising the new brand relationships on social media

Spokes-characters are ‘...animated beings or objects, created to promote a product, service or idea’ (Phillips 1996, p.155). They were first used in the late 1800s when they emerged as registered trademarks, but the use of spokes-characters for marketing communications has since grown, owing to their ability to remind consumers about a product, transfer positive associations to a brand, and give a corporate company a more ‘personal’ face (Callcott and Lee 1995). One example is the Michelin Man, who has served as spokes-character for Michelin tyres since 1898, after starting out in print advertising. Spokes-characters have become important brand representatives, no longer seen as simply entertaining cartoons featured in television and magazine advertisements. Corporations have now extended their use to interactive, social media platforms, where a consumer can be ‘friends’ with a spokes-character via Facebook, read their comments on the latest iPhone release through Twitter, and watch their family histories being documented on YouTube (see Figure 1). The interactions that consumers once had with two-dimensional spokes-characters have undergone significant transformation in the digital space. With spokes-character Facebook pages achieving significant numbers of ‘likes’ and interactions with consumers, one question concerns whether this strategy is creating characters that are more engaging than the brands they represent, and what impact this has on brand outcomes.

Are two threats worse than one? The effects of face race and emotional expression on fear conditioning

Facial cues of racial outgroup or anger mediate fear learning that is resistant to extinction. Whether this resistance is potentiated if fear is conditioned to angry, other race faces has not been established. Two groups of Caucasian participants were conditioned with two happy and two angry face conditional stimuli (CSs). During acquisition, one happy and one angry face were paired with an aversive unconditional stimulus whereas the second happy and angry faces were presented alone. CS face race (Caucasian, African American) was varied between groups. During habituation, electrodermal responses were larger to angry faces regardless of race and declined less to other race faces. Extinction was immediate for Caucasian happy faces, delayed for angry faces regardless of race, and slowest for happy racial outgroup faces. Combining the facial cues of other race and anger does not enhance resistance to extinction of fear.

The changing face of lithium cells

Despite negative press, the future of lithium-based battery chemistries appears positive.