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.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.

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.

Reaction to point and counterpoint : bold adventure or missed opportunity

The draft of the first stage of the national curriculum has now been published. Its final form to be presented in December 2010 should be the centrepiece of Labor’s Educational Revolution. All the other aspects – personal computers, new school buildings, rebates for uniforms and even the MySchool report card – are marginal to the prescription of what is to be taught and learnt in schools. The seven authors in this journal’s Point and Counterpoint (Curriculum Perspectives, 30(1) 2010, pp.53-74) raise a number of both large and small issues in education as a whole, and in science education more particularly. Two of them (Groves and McGarry) make brief reference to earlier attempts to achieve national curriculum in Australia. Those writing from New Zealand and USA will be unaware of just how ambitious this project is for Australia - a bold and overdue educational adventure or a foolish political decision destined to failure, as happened in the later 1970s and the 1990s.

PLDA based speaker recognition on short utterances

This paper investigates the effects of limited speech data in the context of speaker verification using a probabilistic linear discriminant analysis (PLDA) approach. Being able to reduce the length of required speech data is important to the development of automatic speaker verification system in real world applications. When sufficient speech is available, previous research has shown that heavy-tailed PLDA (HTPLDA) modeling of speakers in the i-vector space provides state-of-the-art performance, however, the robustness of HTPLDA to the limited speech resources in development, enrolment and verification is an important issue that has not yet been investigated. In this paper, we analyze the speaker verification performance with regards to the duration of utterances used for both speaker evaluation (enrolment and verification) and score normalization and PLDA modeling during development. Two different approaches to total-variability representation are analyzed within the PLDA approach to show improved performance in short-utterance mismatched evaluation conditions and conditions for which insufficient speech resources are available for adequate system development. The results presented within this paper using the NIST 2008 Speaker Recognition Evaluation dataset suggest that the HTPLDA system can continue to achieve better performance than Gaussian PLDA (GPLDA) as evaluation utterance lengths are decreased. We also highlight the importance of matching durations for score normalization and PLDA modeling to the expected evaluation conditions. Finally, we found that a pooled total-variability approach to PLDA modeling can achieve better performance than the traditional concatenated total-variability approach for short utterances in mismatched evaluation conditions and conditions for which insufficient speech resources are available for adequate system development.

Visual route recognition with a handful of bits

In this paper we use a sequence-based visual localization algorithm to reveal surprising answers to the question, how much visual information is actually needed to conduct effective navigation? The algorithm actively searches for the best local image matches within a sliding window of short route segments or 'sub-routes', and matches sub-routes by searching for coherent sequences of local image matches. In contract to many existing techniques, the technique requires no pre-training or camera parameter calibration. We compare the algorithm's performance to the state-of-the-art FAB-MAP 2.0 algorithm on a 70 km benchmark dataset. Performance matches or exceeds the state of the art feature-based localization technique using images as small as 4 pixels, fields of view reduced by a factor of 250, and pixel bit depths reduced to 2 bits. We present further results demonstrating the system localizing in an office environment with near 100% precision using two 7 bit Lego light sensors, as well as using 16 and 32 pixel images from a motorbike race and a mountain rally car stage. By demonstrating how little image information is required to achieve localization along a route, we hope to stimulate future 'low fidelity' approaches to visual navigation that complement probabilistic feature-based techniques.

Identity and genetic origins : an ethical exploration of the late discovery of adoptive and donor-insemination offspring status

This thesis is an ethical and empirical exploration of the late discovery of genetic origins in two contexts, adoption and sperm donor-assisted conception. This exploration has two interlinked strands of concern. The first is the identification of ‘late discovery’ as a significant issue of concern, deserving of recognition and acknowledgment. The second concerns the ethical implications of late discovery experiences for the welfare of the child. The apparently simple act of recognition of a phenomenon is a precondition to any analysis and critique of it. This is especially important when the phenomenon arises out of social practices that arouse significant debate in ethical and legal contexts. As the new reproductive technologies and some adoption practices remain highly contested, an ethical exploration of this long neglected experience has the potential to offer new insights and perspectives in a range of contexts. It provides an opportunity to revisit developmental debate on the relative merit or otherwise of biological versus social influences, from the perspective of those who have lived this dichotomy in practise. Their experiences are the human face of the effects arising from decisions taken by others to intentionally separate their biological and social worlds, an action which has then been compounded by family and institutional secrecy from birth. This has been accompanied by a failure to ensure that normative standards and values are upheld for them. Following discovery, these factors can be exacerbated by a lack of recognition and acknowledgement of their concerns by family, friends, community and institutions. Late discovery experiences offer valuable insights to inform discussions on the ethical meanings of child welfare, best interests, parental responsibility, duty of care and child identity rights in this and other contexts. They can strengthen understandings of what factors are necessary for a child to be able to live a reasonably happy or worthwhile life.

A toolbox for animal call recognition

Monitoring the natural environment is increasingly important as habit degradation and climate change reduce theworld’s biodiversity.We have developed software tools and applications to assist ecologists with the collection and analysis of acoustic data at large spatial and temporal scales.One of our key objectives is automated animal call recognition, and our approach has three novel attributes. First, we work with raw environmental audio, contaminated by noise and artefacts and containing calls that vary greatly in volume depending on the animal’s proximity to the microphone. Second, initial experimentation suggested that no single recognizer could dealwith the enormous variety of calls. Therefore, we developed a toolbox of generic recognizers to extract invariant features for each call type. Third, many species are cryptic and offer little data with which to train a recognizer. Many popular machine learning methods require large volumes of training and validation data and considerable time and expertise to prepare. Consequently we adopt bootstrap techniques that can be initiated with little data and refined subsequently. In this paper, we describe our recognition tools and present results for real ecological problems.

Towards robust night and day place recognition using visible and thermal imaging

The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

Strategic renewal and competitive advantage in opportunity-driven and conservative new ventures

Strategic renewal has received relatively little attention in the context of new ventures. We examine the relationship among strategic renewal, competitive advantage and performance in opportunity-driven and conservative new ventures. Based on longitudinal data of a random sample of almost 373 new ventures, the link between strategic renewal and performance can be better understood by adding the mediating role of competitive advantage. Our results indicate that increased levels of strategic renewal positively relate to competitive advantage in conservative ventures, but not in opportunity-driven ventures. These findings place a different perspective on the dominant view that entrepreneurs should be opportunity maximizers. It suggests that both conservative and opportunity-driven new ventures can be successful if they follow different paths of strategic renewal in shaping competitive advantage.

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.

Formal complaints of workplace sexual harassment lodged with Australian Human Rights and Equal Opportunity Commissions - 1 July 2009 - 31 December 2009

This report presents an analysis of quantitative data collected from the Australian Human Rights Commission, the Anti-Discrimination Commission of Queensland, the Victorian Equal Opportunity and Human Rights Commission, the Anti-Discrimination Board of New South Wales, the Equal Opportunity Commission of South Australia, the Australian Capital Territory Human Rights Commission, the Equal Opportunity Commission Western Australia, the Northern Territory Anti-Discrimination Commission, and the Office of the Anti-Discrimination Commissioner (Tasmania) (hereafter referred to as the Commissions). The data comprise formal complaints lodged under the various federal, state and territory anti-discrimination laws in the period 1 July 2009 to 31 December 2009 where a complainant had alleged sexual harassment in the area of employment.