Super-resolved faces for improved face recognition from surveillance video advances in biometrics

Characteristics of surveillance video generally include low resolution and poor quality due to environmental, storage and processing limitations. It is extremely difficult for computers and human operators to identify individuals from these videos. To overcome this problem, super-resolution can be used in conjunction with an automated face recognition system to enhance the spatial resolution of video frames containing the subject and narrow down the number of manual verifications performed by the human operator by presenting a list of most likely candidates from the database. As the super-resolution reconstruction process is ill-posed, visual artifacts are often generated as a result. These artifacts can be visually distracting to humans and/or affect machine recognition algorithms. While it is intuitive that higher resolution should lead to improved recognition accuracy, the effects of super-resolution and such artifacts on face recognition performance have not been systematically studied. This paper aims to address this gap while illustrating that super-resolution allows more accurate identification of individuals from low-resolution surveillance footage. The proposed optical flow-based super-resolution method is benchmarked against Baker et al.’s hallucination and Schultz et al.’s super-resolution techniques on images from the Terrascope and XM2VTS databases. Ground truth and interpolated images were also tested to provide a baseline for comparison. Results show that a suitable super-resolution system can improve the discriminability of surveillance video and enhance face recognition accuracy. The experiments also show that Schultz et al.’s method fails when dealing surveillance footage due to its assumption of rigid objects in the scene. The hallucination and optical flow-based methods performed comparably, with the optical flow-based method producing less visually distracting artifacts that interfered with human recognition.

Make-buy decisions in the face of technological change: does industry clockspeed matter?

Some evidence in the area of make-buy decisions for new technologies suggests that it is a good idea for a company to pursue a fairly rigorous ''make'' policy in the early days of a potentially disruptive innovation. Other studies prescribe exactly the opposite, promoting instead a ''buy'' strategy. This paper seeks to bridge the gap between these perspectives by suggesting that both strategies are valid, but that they are most successfully applied in different market environments. The ''make'' prescription may be more suited to either extremely fast or extremely slow rates of technological change, while a ''buy'' strategy might be more appropriate in market sectors where technologies evolve at a medium pace. This paper highlights the importance of industry clockspeed and supplier relationships in make-buy decisions for new technologies, and puts forward two new hypotheses that require empirical testing.

Face recognition across pose on video using eigen light-fields

We propose an approach to employ eigen light-fields for face recognition across pose on video. Faces of a subject are collected from video frames and combined based on the pose to obtain a set of probe light-fields. These probe data are then projected to the principal subspace of the eigen light-fields within which the classification takes place. We modify the original light-field projection and found that it is more robust in the proposed system. Evaluation on VidTIMIT dataset has demonstrated that the eigen light-fields method is able to take advantage of multiple observations contained in the video.

Feature-domain super-resolution framework for gabor-based face and iris recognition

The low resolution of images has been one of the major limitations in recognising humans from a distance using their biometric traits, such as face and iris. Superresolution has been employed to improve the resolution and the recognition performance simultaneously, however the majority of techniques employed operate in the pixel domain, such that the biometric feature vectors are extracted from a super-resolved input image. Feature-domain superresolution has been proposed for face and iris, and is shown to further improve recognition performance by capitalising on direct super-resolving the features which are used for recognition. However, current feature-domain superresolution approaches are limited to simple linear features such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), which are not the most discriminant features for biometrics. Gabor-based features have been shown to be one of the most discriminant features for biometrics including face and iris. This paper proposes a framework to conduct super-resolution in the non-linear Gabor feature domain to further improve the recognition performance of biometric systems. Experiments have confirmed the validity of the proposed approach, demonstrating superior performance to existing linear approaches for both face and iris biometrics.

Energy use, indoor temperature and possible adaptation strategies for air-conditioned office buildings in face of global warming

This paper discusses and summarises a recent systematic study on the implication of global warming on air conditioned office buildings in Australia. Four areas are covered, including analysis of historical weather data, generation of future weather data for the impact study of global warming, projection of building performance under various global warming scenarios, and evaluation of various adaptation strategies under 2070 high global warming conditions. Overall, it is found that depending on the assumed future climate scenarios and the location considered, the increase of total building energy use for the sample Australian office building may range from 0.4 to 15.1%. When the increase of annual average outdoor temperature exceeds 2 °C, the risk of overheating will increase significantly. However, the potential overheating problem could be completely eliminated if internal load density is significantly reduced.

Probabilistic matching of image sets for video-based face recognition

We address the problem of face recognition on video by employing the recently proposed probabilistic linear discrimi-nant analysis (PLDA). The PLDA has been shown to be robust against pose and expression in image-based face recognition. In this research, the method is extended and applied to video where image set to image set matching is performed. We investigate two approaches of computing similarities between image sets using the PLDA: the closest pair approach and the holistic sets approach. To better model face appearances in video, we also propose the heteroscedastic version of the PLDA which learns the within-class covariance of each individual separately. Our experi-ments on the VidTIMIT and Honda datasets show that the combination of the heteroscedastic PLDA and the closest pair approach achieves the best performance.

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.

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.

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.

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.

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.

Anchored deformable face ensemble alignment

At present, many approaches have been proposed for deformable face alignment with varying degrees of success. However, the common drawback to nearly all these approaches is the inaccurate landmark registrations. The registration errors which occur are predominantly heterogeneous (i.e. low error for some frames in a sequence and higher error for others). In this paper we propose an approach for simultaneously aligning an ensemble of deformable face images stemming from the same subject given noisy heterogeneous landmark estimates. We propose that these initial noisy landmark estimates can be used as an “anchor” in conjunction with known state-of-the-art objectives for unsupervised image ensemble alignment. Impressive alignment performance is obtained using well known deformable face fitting algorithms as “anchors.

Challenges for researchers investigating contraceptive use and pregnancy intentions of young women living in urban and rural Australia : face-to-face discussions to increase participation in a web-based survey

Background: It is imperative to understand how to engage young women in research about issues that are important to them. There is limited reliable data on how young women access contraception in Australia especially in rural areas where services may be less available. Objective: This paper identifies the challenges involved in engaging young Australian women aged 18-23 years to participate in a web-based survey on contraception and pregnancy and ensure their ongoing commitment to follow-up web-based surveys. Methods: A group of young women, aged 18-23 years and living in urban and rural New South Wales, Australia, were recruited to participate in face-to-face discussions using several methods of recruitment: direct contact (face-to-face, telephone or email)and snowball sampling by potential participants inviting their friends. All discussions were transcribed verbatim and analyzed using thematic analysis. Results: Twenty young women participated (urban, n=10: mean age 21.6 years; rural, n=10: 20.0 years) and all used computers or smart phones to access the internet on a daily basis. All participants were concerned about the cost of internet access and utilized free access to social media on their mobile phones. Their willingness to participate in a web-based survey was dependent on incentives with a preference for small financial rewards. Most participants were concerned about their personal details and survey responses remaining confidential and secure. The most appropriate survey would take up to 15 minutes to complete, be a mix of short and long questions and eye-catching with bright colours. Questions on the sensitive topics of sexual activity, contraception and pregnancy were acceptable if they could respond with “I prefer not to answer”. Conclusions: There are demographic, participation and survey design challenges in engaging young women in a web-based survey. Based on our findings, future research efforts are needed to understand the full extent of the role social media and incentives play in the decision of young women to participate in web-based research.