V1-inspired features induce a weighted margin in SVMs

Image representations derived from simplified models of the primary visual cortex (V1), such as HOG and SIFT, elicit good performance in a myriad of visual classification tasks including object recognition/detection, pedestrian detection and facial expression classification. A central question in the vision, learning and neuroscience communities regards why these architectures perform so well. In this paper, we offer a unique perspective to this question by subsuming the role of V1-inspired features directly within a linear support vector machine (SVM). We demonstrate that a specific class of such features in conjunction with a linear SVM can be reinterpreted as inducing a weighted margin on the Kronecker basis expansion of an image. This new viewpoint on the role of V1-inspired features allows us to answer fundamental questions on the uniqueness and redundancies of these features, and offer substantial improvements in terms of computational and storage efficiency.

Fourier Lucas-Kanade Algorithm

In this paper we propose a framework for both gradient descent image and object alignment in the Fourier domain. Our method centers upon the classical Lucas & Kanade (LK) algorithm where we represent the source and template/model in the complex 2D Fourier domain rather than in the spatial 2D domain. We refer to our approach as the Fourier LK (FLK) algorithm. The FLK formulation is advantageous when one pre-processes the source image and template/model with a bank of filters (e.g. oriented edges, Gabor, etc.) as: (i) it can handle substantial illumination variations, (ii) the inefficient pre-processing filter bank step can be subsumed within the FLK algorithm as a sparse diagonal weighting matrix, (iii) unlike traditional LK the computational cost is invariant to the number of filters and as a result far more efficient, and (iv) this approach can be extended to the inverse compositional form of the LK algorithm where nearly all steps (including Fourier transform and filter bank pre-processing) can be pre-computed leading to an extremely efficient and robust approach to gradient descent image matching. Further, these computational savings translate to non-rigid object alignment tasks that are considered extensions of the LK algorithm such as those found in Active Appearance Models (AAMs).

Efficient articulated trajectory reconstruction using dynamic programming and filters

This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

Performance configurations over time: implications for growth-and profit-oriented strategies

Entrepreneurship research and practice places emphasis on company growth as a measure of entrepreneurial success. In many cases, there has been a tendency to give growth a very central role, with some researchers even seeing growth as the very essence of entrepreneurship (Cole, 1949; Sexton, 1997; Stevenson & Gumpert, 1991). A large number of empirical studies of the performance of young and/or small firms use growth as the dependent variable (see reviews by Ardishvili, Cardozo, Harmon, & Vadakath, 1998; Delmar, 1997; Wiklund, 1998). By contrast, the two most prominent views of strategic management – strategic positioning (Porter, 1980) and the resource-based view (Barney, 1991; Wernerfelt, 1984) – are both concerned with achieving competitive advantage and regard achieving economic rents and profitability relative to other competitors as the central measures of firm performance. Strategic entrepreneurship integrates these two perspectives and is simultaneously concerned with opportunity seeking and advantage seeking (Hitt, Ireland, Camp, & Sexton, 2002; Ireland, Hitt, & Sirmon, 2003). Consequently, both company growth and relative profitability are together relevant measures of firm performance in the domain of strategic entrepreneurship.

Oriented graphitic carbon films for hydrogen gas sensors

An oriented graphitic nanostructured carbon film has been employed as a conductometric hydrogen gas sensor. The carbon film was energetically deposited using a filtered cathodic vacuum arc with a -75 V bias applied to a stainless steel grid placed 1cm from the surface of the Si substrate. The substrate was heated to 400°C prior to deposition. Electron microscopy showed evidence that the film consisted largely of vertically oriented graphitic sheets and had a density of 2.06 g/cm3. 76% of the atoms were bonded in sp2 or graphitic configurations. A change in the device resistance of >; 1.5% was exhibited upon exposure to 1 % hydrogen gas (in synthetic, zero humidity air) at 100°C. The time for the sensor resistance to increase by 1.5 % under these conditions was approximately 60 s and the baseline (zero hydrogen exposure) resistance remained constant to within 0.01% during and after the hydrogen exposures.

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

GrabCutSFM : how 3D information improves unsupervised object segmentation

In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called Grab- CutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.

Visual code annotations for cyberphysical programming

User interfaces for source code editing are a crucial component in any software development environment, and in many editors visual annotations (overlaid on the textual source code) are used to provide important contextual information to the programmer. This paper focuses on the real-time programming activity of ‘cyberphysical’ programming, and considers the type of visual annotations which may be helpful in this programming context.

The ability of YSR DSM-oriented depression scales to predict DSM-IV depression in young adults : a longitudinal study

Background The Achenbach child behaviour checklist (CBCL/YSR) is a widely used screening tool for affective problems. Several studies report good association between the checklists and psychiatric diagnoses; although with varying degrees of agreement. Most are cross-sectional studies involving adolescents referred to mental health services. This paper aims to evaluate the performance of the youth self report (YSR) empirical and DSM-oriented internalising scales in predicting later depressive disorders in young adults. Methods Sample was 2431 young adults from an Australian birth cohort study. The strength of association between the empirical and DSM-oriented scales assessed at 14 and 21 years and structured-interview derived depression in young adulthood (18 to 22 years) were tested using odds ratios, ROC analyses and related diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values). Results Adolescents with internalising symptoms were twice (OR 2.3, 95%CI 1.7 to 3.1) as likely to be diagnosed with DSM-IV depression by age 21. Use of DSM-oriented depressive scales did not improve the concordance between the internalising behaviour and DSM-IV diagnosed depression at age 14 (ORs ranged from 1.9 to 2.5). Limitations Some loss to follow-up over the 7-year gap between the two waves of follow-up. Conclusion DSM-oriented scales perform no better than the standard internalising or anxious/depressed scales in identifying young adults with later DSM-IV depressive disorder.

Predicting depressive and anxiety disorders with the YASR internalising scales (empirical and DSM-oriented)

Background The Achenbach problem behaviour scales (CBCL/YSR) are widely used. The DSM-oriented anxiety and depression scales have been created to improve concordance between Achenbach’s internalising scales and DSM-IV depression and anxiety. To date no study has examined the concurrent utility of the young adult (YASR) internalising scales, either the empirical or newly developed DSM-oriented depressive or anxiety scales. Methods A sample of 2,551 young adults, aged 18–23 years, from an Australian cohort study. The association between the empirical and DSM-oriented anxiety and depression scales were individually assessed against DSMIV depression and anxiety diagnoses derived from structured interview. Odds ratios, ROC analyses and diagnostic efficiency tests (sensitivity, specificity, positive and negative predictive values) were used to report findings. Results YASR empirical internalising scale predicted DSM-IV mood disorders (depression OR = 6.9, 95% CI 5.0–9.5; anxiety OR = 5.1, 95% CI 3.8–6.7) in the previous 12 months. DSM-oriented depressive or anxiety scales did not appear to improve the concordance with DSM-IV diagnosed depression or anxiety. The internalising scales were much more effective at identifying those with comorbid depression and anxiety, with Ors between 10.1 and 21.7 depending on the internalising scale used. Conclusion DSM-oriented scales perform no better than the standard internalising in identifying young adults with DSM-IV mood or anxiety disorder.

A concept-based retrieval method for entity-oriented search

Entity-oriented retrieval aims to return a list of relevant entities rather than documents to provide exact answers for user queries. The nature of entity-oriented retrieval requires identifying the semantic intent of user queries, i.e., understanding the semantic role of query terms and determining the semantic categories which indicate the class of target entities. Existing methods are not able to exploit the semantic intent by capturing the semantic relationship between terms in a query and in a document that contains entity related information. To improve the understanding of the semantic intent of user queries, we propose concept-based retrieval method that not only automatically identifies the semantic intent of user queries, i.e., Intent Type and Intent Modifier but introduces concepts represented by Wikipedia articles to user queries. We evaluate our proposed method on entity profile documents annotated by concepts from Wikipedia category and list structure. Empirical analysis reveals that the proposed method outperforms several state-of-the-art approaches.

Privacy oriented access control for electronic health records

Information privacy is a critical success/failure factor in information technology supported healthcare (eHealth). eHealth systems utilise electronic health records (EHR) as the main source of information, thus, implementing appropriate privacy preserving methods for EHRs is vital for the proliferation of eHealth. Whilst information privacy may be a fundamental requirement for eHealth consumers, healthcare professionals demand non-restricted access to patient information for improved healthcare delivery, thus, creating an environment where stakeholder requirements are contradictory. Therefore, there is a need to achieve an appropriate balance of requirements in order to build successful eHealth systems. Towards achieving this balance, a new genre of eHealth systems called Accountable-eHealth (AeH) systems has been proposed. In this paper, an access control model for EHRs is presented that can be utilised by AeH systems to create information usage policies that fulfil both stakeholders’ requirements. These policies are used to accomplish the aforementioned balance of requirements creating a satisfactory eHealth environment for all stakeholders. The access control model is validated using a Web based prototype as a proof of concept.

Street computing : towards an integrated open data Application Programming Interface (API) for cities

This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing Workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer- Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges, and foundations of this research trajectory. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarizes related work in this field of interest. We conclude by introducing the papers that have been contributed to this special issue.

Advance transit oriented development typology : case study in Brisbane, Australia

Internationally, transit oriented development (TOD) is characterised by moderate to high density development with diverse land use patterns and well connected street networks centred around high frequency transit stops (bus and rail). Although different TOD typologies have been developed in different contexts, they are based on subjective evaluation criteria derived from the context in which they are built and typically lack a validation measure. Arguably there exist sets of TOD characteristics that perform better in certain contexts, and being able to optimise TOD effectiveness would facilitate planning and supporting policy development. This research utilises data from census collection districts (CCDs) in Brisbane with different sets of TOD attributes measured across six objectively quantified built environmental indicators: net employment density, net residential density, land use diversity, intersection density, cul-de-sac density, and public transport accessibility. Using these measures, a Two Step Cluster Analysis was conducted to identify natural groupings of the CCDs with similar profiles, resulting in four unique TOD clusters: (a) residential TODs, (b) activity centre TODs, (c) potential TODs, and; (d) TOD non-suitability. The typologies are validated by estimating a multinomial logistic regression model in order to understand the mode choice behaviour of 10,013 individuals living in these areas. Results indicate that in comparison to people living in areas classified as residential TODs, people who reside in non-TOD clusters were significantly less likely to use public transport (PT) (1.4 times), and active transport (4 times) compared to the car. People living in areas classified as potential TODs were 1.3 times less likely to use PT, and 2.5 times less likely to use active transport compared to using the car. Only a little difference in mode choice behaviour was evident between people living in areas classified as residential TODs and activity centre TODs. The results suggest that: (a) two types of TODs may be suitable for classification and effect mode choice in Brisbane; (b) TOD typology should be developed based on their TOD profile and performance matrices; (c) both bus stop and train station based TODs are suitable for development in Brisbane.

A process-oriented approach to supporting Off-site Manufacture in construction projects

It is well-known that the use of off-site manufacture (OSM) techniques can assist in timely completion of a construction project though the utilisation of such techniques may have other disadvantages. Currently, OSM uptake within the Australian construction industry is limited. To successfully incorporate OSM practices within a construction project, it is crucial to understand the impact of OSM adoption on the processes used during a construction project. This paper presents how a systematic process-oriented approach may be able to support OSM utilisation within a construction project. Process modelling, analysis and automation techniques which are well-known within the Business Process Management (BPM) discipline have been applied to develop a collection of construction process models that represent the end-to-end generic construction value chain. The construction value chain enables researchers to identify key activities, resources, data, and stakeholders involved in construction processes in each defined construction phase. The collection of construction process models is then used as a basis for identification of potential OSM intervention points in collaboration with domain experts from the Australian construction industry. This ensures that the resulting changes reflect the needs of various stakeholders within the construction industry and have relevance in practice. Based on the input from the domain experts, these process models are further refined and operational requirements are taken into account to develop a prototype process automation (workflow) system that can support and coordinate OSM-related process activities. The resulting workflow system also has the potential to integrate with other IT solutions used within the construction industry (e.g., BIM, Acconex). As such, the paper illustrates the role that process-oriented thinking can play in assisting OSM adoption within the industry.