Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

Disproportionate over-representation of Indigenous students in New South Wales government special schools

A significant gap exists in the Australian research literature on the disproportionate over-representation of minority groups in special education. The aim of this paper is to make a contribution to the research evidence-base by sketching an outline of the issue as it presents in Australia’s largest education system in the state of New South Wales. Findings from this research show that Indigenous students are equally represented in special schools enrolling students with autism, physical, sensory, and intellectual disabilities, but significantly over-represented in special schools enrolling students under the categories of emotional disturbance, behaviour disorder and juvenile detention. Factors that might influence the disproportionate over-representation of Indigenous children and young people are discussed, and based on these observations, some practical implications for policy and practice are provided.

Supplementary Information : Hogan, Holland, Holloway, Petit and Read : Read Classification for Next Generation Sequencing, ESANN 2013, April 2013

This item provides supplementary materials for the paper mentioned in the title, specifically a range of organisms used in the study. The full abstract for the main paper is as follows: Next Generation Sequencing (NGS) technologies have revolutionised molecular biology, allowing clinical sequencing to become a matter of routine. NGS data sets consist of short sequence reads obtained from the machine, given context and meaning through downstream assembly and annotation. For these techniques to operate successfully, the collected reads must be consistent with the assumed species or species group, and not corrupted in some way. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans,with some strains exhibiting antibiotic resistance. In this paper, we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from alternative pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.

Feasibility of agent-based modelling of articular cartilage including a conceptual representation of its structure

Articular cartilage is a complex structure with an architecture in which fluid-swollen proteoglycans constrained within a 3D network of collagen fibrils. Because of the complexity of the cartilage structure, the relationship between its mechanical behaviours at the macroscale level and its components at the micro-scale level are not completely understood. The research objective in this thesis is to create a new model of articular cartilage that can be used to simulate and obtain insight into the micro-macro-interaction and mechanisms underlying its mechanical responses during physiological function. The new model of articular cartilage has two characteristics, namely: i) not use fibre-reinforced composite material idealization ii) Provide a framework for that it does probing the micro mechanism of the fluid-solid interaction underlying the deformation of articular cartilage using simple rules of repartition instead of constitutive / physical laws and intuitive curve-fitting. Even though there are various microstructural and mechanical behaviours that can be studied, the scope of this thesis is limited to osmotic pressure formation and distribution and their influence on cartilage fluid diffusion and percolation, which in turn governs the deformation of the compression-loaded tissue. The study can be divided into two stages. In the first stage, the distributions and concentrations of proteoglycans, collagen and water were investigated using histological protocols. Based on this, the structure of cartilage was conceptualised as microscopic osmotic units that consist of these constituents that were distributed according to histological results. These units were repeated three-dimensionally to form the structural model of articular cartilage. In the second stage, cellular automata were incorporated into the resulting matrix (lattice) to simulate the osmotic pressure of the fluid and the movement of water within and out of the matrix; following the osmotic pressure gradient in accordance with the chosen rule of repartition of the pressure. The outcome of this study is the new model of articular cartilage that can be used to simulate and study the micromechanical behaviours of cartilage under different conditions of health and loading. These behaviours are illuminated at the microscale level using the socalled neighbourhood rules developed in the thesis in accordance with the typical requirements of cellular automata modelling. Using these rules and relevant Boundary Conditions to simulate pressure distribution and related fluid motion produced significant results that provided the following insight into the relationships between osmotic pressure gradient and associated fluid micromovement, and the deformation of the matrix. For example, it could be concluded that: 1. It is possible to model articular cartilage with the agent-based model of cellular automata and the Margolus neighbourhood rule. 2. The concept of 3D inter connected osmotic units is a viable structural model for the extracellular matrix of articular cartilage. 3. Different rules of osmotic pressure advection lead to different patterns of deformation in the cartilage matrix, enabling an insight into how this micromechanism influences macromechanical deformation. 4. When features such as transition coefficient were changed, permeability (representing change) is altered due to the change in concentrations of collagen, proteoglycans (i.e. degenerative conditions), the deformation process is impacted. 5. The boundary conditions also influence the relationship between osmotic pressure gradient and fluid movement at the micro-scale level. The outcomes are important to cartilage research since we can use these to study the microscale damage in the cartilage matrix. From this, we are able to monitor related diseases and their progression leading to potential insight into drug-cartilage interaction for treatment. This innovative model is an incremental progress on attempts at creating further computational modelling approaches to cartilage research and other fluid-saturated tissues and material systems.

Representation of assertions in clinical free-­text using SNOMED CT

Information retrieval (IR) by clinicians in the healthcare setting is critical for informing clinical decision-making. However, a large part of this information is in the form of free-text and inhibits clinical decision support and effective healthcare services. This makes meaningful use of clinical free-­text in electronic health records (EHRs) for patient care a difficult task. Within the context of IR, given a repository of free-­text clinical reports, one might want to retrieve and analyse data for patients who have a known clinical finding.

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.

The minority report : disproportionate representation in Australia’s largest education system

The overrepresentation of students from minority ethnic groups in separate special education settings has been extensively documented in North America, yet little research exists for Australian school systems. To address this gap, we systematically analyzed 13 years of enrolment data from the state of New South Wales. Stark differences are seen in patterns of enrolment between Indigenous students, students from a Language Background Other than English (LBOTE), and non-Indigenous English speaking students. Moreover, these differences are increasing. While enrollments of Indigenous students in separate settings increased faster across time than did enrollments of Indigenous students in mainstream, enrollments of LBOTE students in mainstream increased faster than did enrollments of LBOTE students in separate settings.

I-vector based speaker recognition using advanced channel compensation techniques

This paper investigates advanced channel compensation techniques for the purpose of improving i-vector speaker verification performance in the presence of high intersession variability using the NIST 2008 and 2010 SRE corpora. The performance of four channel compensation techniques: (a) weighted maximum margin criterion (WMMC), (b) source-normalized WMMC (SN-WMMC), (c) weighted linear discriminant analysis (WLDA), and; (d) source-normalized WLDA (SN-WLDA) have been investigated. We show that, by extracting the discriminatory information between pairs of speakers as well as capturing the source variation information in the development i-vector space, the SN-WLDA based cosine similarity scoring (CSS) i-vector system is shown to provide over 20% improvement in EER for NIST 2008 interview and microphone verification and over 10% improvement in EER for NIST 2008 telephone verification, when compared to SN-LDA based CSS i-vector system. Further, score-level fusion techniques are analyzed to combine the best channel compensation approaches, to provide over 8% improvement in DCF over the best single approach, (SN-WLDA), for NIST 2008 interview/ telephone enrolment-verification condition. Finally, we demonstrate that the improvements found in the context of CSS also generalize to state-of-the-art GPLDA with up to 14% relative improvement in EER for NIST SRE 2010 interview and microphone verification and over 7% relative improvement in EER for NIST SRE 2010 telephone verification.

Impact of Wolbachia on infection with chikungunya and yellow fever viruses in the mosquito vector Aedes aegypti

Incidence of disease due to dengue (DENV), chikungunya (CHIKV) and yellow fever (YFV) viruses is increasing in many parts of the world. The viruses are primarily transmitted by Aedes aegypti, a highly domesticated mosquito species that is notoriously difficult to control. When transinfected into Ae. aegypti, the intracellular bacterium Wolbachia has recently been shown to inhibit replication of DENVs, CHIKV, malaria parasites and filarial nematodes, providing a potentially powerful biocontrol strategy for human pathogens. Because the extent of pathogen reduction can be influenced by the strain of bacterium, we examined whether the wMel strain of Wolbachia influenced CHIKV and YFV infection in Ae. aegypti. Following exposure to viremic blood meals, CHIKV infection and dissemination rates were significantly reduced in mosquitoes with the wMel strain of Wolbachia compared to Wolbachia-uninfected controls. However, similar rates of infection and dissemination were observed in wMel infected and non-infected Ae. aegypti when intrathoracic inoculation was used to deliver virus. YFV infection, dissemination and replication were similar in wMel-infected and control mosquitoes following intrathoracic inoculations. In contrast, mosquitoes with the wMelPop strain of Wolbachia showed at least a 10(4) times reduction in YFV RNA copies compared to controls. The extent of reduction in virus infection depended on Wolbachia strain, titer and strain of the virus, and mode of exposure. Although originally proposed for dengue biocontrol, our results indicate a Wolbachia-based strategy also holds considerable promise for YFV and CHIKV suppression.

Some extensions to representation and encoding of structure in models of distributional semantics

This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.

The remediation of the personal photograph and the politics of self-representation in digital storytelling

Over the past couple of decades, the cultural field formerly known as ‘domestic’, and later ‘personal’ photography has been remediated and transformed as part of the social web, with its convergence of personal expression, interpersonal communication, and online social networks (most recently via platforms like Flickr, Facebook and Twitter). Meanwhile, the Digital Storytelling movement (involving the workshop-based production of short autobiographical videos) from its beginnings in the mid 1990s relied heavily on the narrative power of the personal photograph, often sourced from family albums, and later from online archives. This paper addresses the new issues arising for the politics of self-representation and personal photography in the era of social media, focusing particularly on the consequences of online image-sharing. It discusses in detail the practices of selection, curation, manipulation and editing of personal photographic images among a group of activist-oriented queer digital storytellers who have in common a stated desire to share their personal stories in pursuit of social change, and whose stories often aim to address both intimate and antagonistic publics.

Improving short utterance based I-vector speaker recognition using source and utterance-duration normalization techniques

A significant amount of speech is typically required for speaker verification system development and evaluation, especially in the presence of large intersession variability. This paper introduces a source and utterance duration normalized linear discriminant analysis (SUN-LDA) approaches to compensate session variability in short-utterance i-vector speaker verification systems. Two variations of SUN-LDA are proposed where normalization techniques are used to capture source variation from both short and full-length development i-vectors, one based upon pooling (SUN-LDA-pooled) and the other on concatenation (SUN-LDA-concat) across the duration and source-dependent session variation. Both the SUN-LDA-pooled and SUN-LDA-concat techniques are shown to provide improvement over traditional LDA on NIST 08 truncated 10sec-10sec evaluation conditions, with the highest improvement obtained with the SUN-LDA-concat technique achieving a relative improvement of 8% in EER for mis-matched conditions and over 3% for matched conditions over traditional LDA approaches.

A novel representation of bioacoustic events for content-based search in field audio data

Bioacoustic data can provide an important base for environmental monitoring. To explore a large amount of field recordings collected, an automated similarity search algorithm is presented in this paper. A region of an audio defined by frequency and time bounds is provided by a user; the content of the region is used to construct a query. In the retrieving process, our algorithm will automatically scan through recordings to search for similar regions. In detail, we present a feature extraction approach based on the visual content of vocalisations – in this case ridges, and develop a generic regional representation of vocalisations for indexing. Our feature extraction method works best for bird vocalisations showing ridge characteristics. The regional representation method allows the content of an arbitrary region of a continuous recording to be described in a compressed format.

Recognising facial expressions with noisy data

Techniques to improve the automated analysis of natural and spontaneous facial expressions have been developed. The outcome of the research has applications in several fields including national security (eg: expression invariant face recognition); education (eg: affect aware interfaces); mental and physical health (eg: depression and pain recognition).

Writing the oriental woman : an examination of the representation of Japanese women in contemporary Australian crime fiction

This study considers the challenges in representing women from other cultures in the crime fiction genre. The study is presented in two parts; an exegesis and a creative practice component consisting of a full length crime fiction novel, Batafurai. The exegesis examines the historical period of a section of the novel—post-war Japan—and how the area of research known as Occupation Studies provides an insight into the conditions of women during this period. The exegesis also examines selected postcolonial theory and its exposition of representations of the 'other' as a western construct designed to serve Eurocentric ends. The genre of crime fiction is reviewed, also, to determine how characters purportedly representing Oriental cultures are constricted by established stereotypes. Two case studies are examined to investigate whether these stereotypes are still apparent in contemporary Australian crime fiction. Finally, I discuss my own novel, Batafurai, to review how I represented people of Asian background, and whether my attempts to resist stereotype were successful. My conclusion illustrates how novels written in the crime fiction genre are reliant on strategies that are action-focused, rather than character-based, and thus often use easily recognizable types to quickly establish frameworks for their stories. As a sub-set of popular fiction, crime fiction has a tendency to replicate rather than challenge established stereotypes. Where it does challenge stereotypes, it reflects a territory that popular culture has already visited, such as the 'female', 'black' or 'gay' detective. Crime fiction also has, as one of its central concerns, an interest in examining and reinforcing the notion of societal order. It repeatedly demonstrates that crime either does not pay or should not pay. One of the ways it does this is to contrast what is 'good', known and understood with what is 'bad', unknown, foreign or beyond our normal comprehension. In western culture, the east has traditionally been employed as the site of difference, and has been constantly used as a setting of contrast, excitement or fear. Crime fiction conforms to this pattern, using the east to add a richness and depth to what otherwise might become a 'dry' tale. However, when used in such a way, what is variously eastern, 'other' or Oriental can never be paramount, always falling to secondary side of the binary opposites (good/evil, known/unknown, redeemed/doomed) at work. In an age of globalisation, the challenge for contemporary writers of popular fiction is to be responsive to an audience that demands respect for all cultures. Writers must demonstrate that they are sensitive to such concerns and can skillfully manage the tensions caused by the need to deliver work that operates within the parameters of the genre, and the desire to avoid offence to any cultural or ethnic group. In my work, my strategy to manage these tensions has been to create a back-story for my characters of Asian background, developing them above mere genre types, and to situate them with credibility in time and place through appropriate historical research.