3D ellipsoid fitting for multi-view gait recognition

Gait recognition approaches continue to struggle with challenges including view-invariance, low-resolution data, robustness to unconstrained environments, and fluctuating gait patterns due to subjects carrying goods or wearing different clothes. Although computationally expensive, model based techniques offer promise over appearance based techniques for these challenges as they gather gait features and interpret gait dynamics in skeleton form. In this paper, we propose a fast 3D ellipsoidal-based gait recognition algorithm using a 3D voxel model derived from multi-view silhouette images. This approach directly solves the limitations of view dependency and self-occlusion in existing ellipse fitting model-based approaches. Voxel models are segmented into four components (left and right legs, above and below the knee), and ellipsoids are fitted to each region using eigenvalue decomposition. Features derived from the ellipsoid parameters are modeled using a Fourier representation to retain the temporal dynamic pattern for classification. We demonstrate the proposed approach using the CMU MoBo database and show that an improvement of 15-20% can be achieved over a 2D ellipse fitting baseline.

Gait energy volumes and frontal gait recognition using depth images

Gait energy images (GEIs) and its variants form the basis of many recent appearance-based gait recognition systems. The GEI combines good recognition performance with a simple implementation, though it suffers problems inherent to appearance-based approaches, such as being highly view dependent. In this paper, we extend the concept of the GEI to 3D, to create what we call the gait energy volume, or GEV. A basic GEV implementation is tested on the CMU MoBo database, showing improvements over both the GEI baseline and a fused multi-view GEI approach. We also demonstrate the efficacy of this approach on partial volume reconstructions created from frontal depth images, which can be more practically acquired, for example, in biometric portals implemented with stereo cameras, or other depth acquisition systems. Experiments on frontal depth images are evaluated on an in-house developed database captured using the Microsoft Kinect, and demonstrate the validity of the proposed approach.

Compressive sensing for gait recognition

Compressive Sensing (CS) is a popular signal processing technique, that can exactly reconstruct a signal given a small number of random projections of the original signal, provided that the signal is sufficiently sparse. We demonstrate the applicability of CS in the field of gait recognition as a very effective dimensionality reduction technique, using the gait energy image (GEI) as the feature extraction process. We compare the CS based approach to the principal component analysis (PCA) and show that the proposed method outperforms this baseline, particularly under situations where there are appearance changes in the subject. Applying CS to the gait features also avoids the need to train the models, by using a generalised random projection.

Pattern recognition using invariants defined from higher order spectra - one-dimensional inputs

A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.

On the behaviour of higher-order spectral features for object recognition in the presence of various types of noise

This paper presents results on the robustness of higher-order spectral features to Gaussian, Rayleigh, and uniform distributed noise. Based on cluster plots and accuracy results for various signal to noise conditions, the higher-order spectral features are shown to be better than moment invariant features.

Automated recognition of drunk driving on highways from video sequences

A new method for the detection of abnormal vehicle trajectories is proposed. It couples optical flow extraction of vehicle velocities with a neural network classifier. Abnormal trajectories are indicative of drunk or sleepy drivers. A single feature of the vehicle, eg., a tail light, is isolated and the optical flow computed only around this feature rather than at each pixel in the image.

High speed rail and regional competitiveness

The presence of High Speed Rail (HSR) systems influences market shares of road and air transport, and the development of cities and regions they serve. With the deployment of HSR infrastructure, changes in accessibility have occurred. These changes have lead researchers to investigate effects on the economic and spatial derived variables. Contention exists when managing the trade off between efficiency, and access points which are usually in the range of hundreds of kilometres apart. In short, it is argued that intermediate cities, bypassed by HSR services, suffer a decline in their accessibility and developmental opportunities. The present Chapter will analyse possible impacts derived from the presence of HSR infrastructure. In particular, it will consider small and medium agglomerations in the vicinity of HSR corridors, not always served by HSR stations. Thus, a methodology is developed to quantify accessibility benefits and their distribution. These benefits will be investigated in relation to different rail transit strategies integrating HSR infrastructure where a HSR station cannot be positioned. These strategies are selected principally for the type of service offered: (i) cadenced, (ii) express, (iii) frequent or (iv) non-stopping. Furthermore, to ground the theoretical approach linking accessibility and competitiveness, a case study in the North-Eastern Italian regions will be used for the application of the accessibility distributive patterns between the HSR infrastructure and the selected strategies. Results indicate that benefits derive from well informed decisions on HSR station positioning and the appropriate blend of complementary services in the whole region to interface HSR infrastructure. The results are significant for all countries in Europe and worldwide, not only for investing in HSR infrastructure, but mostly in terms of building territorial cohesion, while seeking international recognition for developing successful new technology and systems.

Visual voice activity detection using frontal versus profile views

Visual activity detection of lip movements can be used to overcome the poor performance of voice activity detection based solely in the audio domain, particularly in noisy acoustic conditions. However, most of the research conducted in visual voice activity detection (VVAD) has neglected addressing variabilities in the visual domain such as viewpoint variation. In this paper we investigate the effectiveness of the visual information from the speaker’s frontal and profile views (i.e left and right side views) for the task of VVAD. As far as we are aware, our work constitutes the first real attempt to study this problem. We describe our visual front end approach and the Gaussian mixture model (GMM) based VVAD framework, and report the experimental results using the freely available CUAVE database. The experimental results show that VVAD is indeed possible from profile views and we give a quantitative comparison of VVAD based on frontal and profile views The results presented are useful in the development of multi-modal Human Machine Interaction (HMI) using a single camera, where the speaker’s face may not always be frontal.

Which older women could benefit from interventions to decrease sitting time and increase physical activity?

In addition to the well-known health risks associated with lack of physical activity (PA), evidence is emerging about the health risks of sedentary behaviour (sitting). Research about patterns and correlates of sitting and PA in older women is scarce. METHODS: Self-report data from 6,116 women aged 76-81 years were collected as part of the Australian Longitudinal Study on Woman’s Health. Linear regression models were computed to examine whether demographic, social and health factors were associated with sitting and PA. RESULTS: Women who did no PA sat more than women who did any PA (p<0.001). Seven correlates were associated with sitting and PA (p<0.05). Five of these were associated with more sitting and less PA: three health-related (BMI, chronic conditions, anxiety/depression) and two social correlates (caring duties, volunteering). One demographic (being from another English-speaking country) and one social correlate (more social interaction) were associated with more sitting and more PA. Four correlates, two demographic (living in a city; post-high school education), one social (being single), and one health-related correlate (dizziness/loss of balance) were associated with more sitting only. Two other health-related correlates (stiff/painful joints; feet problems) were associated with less PA only. CONCLUSION: Sedentary behaviour and PA are distinct behaviours in older Australian women. Information about the correlates of both behaviours can be used to identify population groups who might benefit from interventions to reduce sedentary behaviour and/or increase PA.

Spatial sciences/ surveying student BEB801 project Capstone Mini-Conference 2011

Project as a Capstone Learning Unit: Courses of the QUT Faculty of BEE seek to enable students to practice as professionals in their respective disciplines. A major part of such practice is the instigation, management,monitoring, and reporting on an urban development project. This unit offers the student a capstone learning experience near the end of their fourth year of undergraduate study. Expose the student to a set of integrated activities, each building upon the preceding, and culminating in a 'completed' project. Students apply skills and knowledge attained earlier in the course and develop new abilities for application to a real-world problem, industry or research based, to simulate the design, development and management of a project solution. These 10-12minute seminar presentations comprise the mini-conference event that are of benefit to the wider surveying and spatial science industry.

Regenerateengageexperiment in 2011! - News from Spatial Science Discipline at QUT

Abstract: Goals and potential impacts of QUT corporate Blueprint3 framework, university has made significant investments in physical infrastructure, and investments to improve staff profiles, particularly in relation to science, technology, engineering, and mathematics (STEM) disciplines. The most significant physical change to the Faculty’s infrastructure has seen new workshop and teaching and research spaces located in Science and Technology precinct under construction. Also includes Alumni news, input and output numbers Spatial Science discussion, Work Integrated Learning (WIL) in 2011, some key teaching administrative dates in 2011.

Spatial Science News from QUT April 2011

Multiple awards for Spatial/Surveying lecturer, raising entry quality and commencing numbers at QUT, Gardens Point rapt in promise of things to come, STEM building progress.

Spatial sciences/ surveying student BEB801 project Capstone Mini-Conference 2011

Project as a Capstone Learning Unit: Courses of the QUT Faculty of BEE seek to enable students to practice as professionals in their respective disciplines. A major part of such practice is the instigation, management,monitoring, and reporting on an urban development project. This unit offers the student a capstone learning experience near the end of their fourth year of undergraduate study. Expose the student to a set of integrated activities, each building upon the preceding, and culminating in a 'completed' project. Students apply skills and knowledge attained earlier in the course and develop new abilities for application to a real-world problem, industry or research based, to simulate the design, development and management of a project solution. These 10-12minute seminar presentations comprise the mini-conference event that are of benefit to the wider surveying and spatial science industry. Additionally Includes MAPMYTOWN 2010, Bell Darling Downs, summary of QUT contributions.

Emergency health services : demand and service delivery models. Monograph 1: literature review and activity trends

Emergency Health Services (EHS), encompassing hospital-based Emergency Departments (ED) and pre-hospital ambulance services, are a significant and high profile component of Australia’s health care system and congestion of these, evidenced by physical overcrowding and prolonged waiting times, is causing considerable community and professional concern. This concern relates not only to Australia’s capacity to manage daily health emergencies but also the ability to respond to major incidents and disasters. EHS congestion is a result of the combined effects of increased demand for emergency care, increased complexity of acute health care, and blocked access to ongoing care (e.g. inpatient beds). Despite this conceptual understanding there is a lack of robust evidence to explain the factors driving increased demand, or how demand contributes to congestion, and therefore public policy responses have relied upon limited or unsound information. The Emergency Health Services Queensland (EHSQ) research program proposes to determine the factors influencing the growing demand for emergency health care and to establish options for alternative service provision that may safely meet patient’s needs. The EHSQ study is funded by the Australian Research Council (ARC) through its Linkage Program and is supported financially by the Queensland Ambulance Service (QAS). This monograph is part of a suite of publications based on the research findings that examines the existing literature, and current operational context. Literature was sourced using standard search approaches and a range of databases as well as a selection of articles cited in the reviewed literature. Public sources including the Australian Institute of Health and Welfare (AIHW), the Council of Ambulance Authorities (CAA) Annual Reports, Australian Bureau of Statistics (ABS) and Department of Health and Ageing (DoHA) were examined for trend data across Australia.

Nobody says no : student self-censorship in a collaborative knowledge building activity

This paper explores student self-censorship within an online learning environment. Self-censorship in group activity can be seen as a two-edged sword. While it can be advantageous that a student censor personal frustration and angst when working with others, if the self-censorship impacts on the cognitive contribution a student makes then this may significantly impact upon the overall quality of the group’s collective knowledge artefact. This paper reports on a study where it was found that students had self censored both their feelings and ideas as they collaboratively worked together.