Kernel analysis on Grassmann manifolds for action recognition

Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

Image Region Salience for Improving Appearance-Based Place Recognition using a Supervised Classifier System

Many state of the art vision-based Simultaneous Localisation And Mapping (SLAM) and place recognition systems compute the salience of visual features in their environment. As computing salience can be problematic in radically changing environments new low resolution feature-less systems have been introduced, such as SeqSLAM, all of which consider the whole image. In this paper, we implement a supervised classifier system (UCS) to learn the salience of image regions for place recognition by feature-less systems. SeqSLAM only slightly benefits from the results of training, on the challenging real world Eynsham dataset, as it already appears to filter less useful regions of a panoramic image. However, when recognition is limited to specific image regions performance improves by more than an order of magnitude by utilising the learnt image region saliency. We then investigate whether the region salience generated from the Eynsham dataset generalizes to another car-based dataset using a perspective camera. The results suggest the general applicability of an image region salience mask for optimizing route-based navigation applications.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Working with refugee survivors of torture and trauma : an opportunity for vicarious posttraumatic growth

Clinical work with people who have survived trauma carries a risk of vicarious traumatisation for the service provider, but also the potential for vicarious posttraumatic growth. Despite growing interest in this area, the effects of working with survivors of refugee-related trauma have remained relatively unexplored. The aim of the current study was to examine the lived experiences of people working on a daily basis with survivors of torture and trauma who had sought refuge in Australia. Seventeen clinical, administrative, and managerial staff from a not-for-profit organisation participated in a semi-structured interview that was later analysed using interpretive phenomenological analysis. Analysis of the data demonstrated that the entire sample reported symptoms of vicarious trauma (e.g., strong emotional reactions, intrusive images, shattering of existing beliefs) as well as vicarious posttraumatic growth (e.g., forming new relationships, increased self-understanding, greater appreciation of life). Moreover, effortful meaning making processes appeared to facilitate such positive changes. Reduction in the risks associated with this work, enhancement of clinician well-being, and improvement of therapeutic outcomes is a shared responsibility of the organisation and clinician. Without negating the distress of trauma work, clinicians are encouraged to more deeply consider the unique positive outcomes that supporting survivors can provide.

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.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.

Regional characteristics, opportunity perception and entrepreneurial activities

This paper seeks to better understand the link between regional characteristics and individual entrepreneurship. We combine individual-level GEM data for Western Germany with regional-level data, using multi-level analysis to test our hypotheses. We find no direct link between regional knowledge creation, the economic context and an entrepreneurial culture on the one side and individual business start-up intentions and start-up activity on the other side. However our findings point to the importance of an indirect effect of regional characteristics as knowledge creation, the economic context and an entrepreneurial culture have an effect on the individual perception of founding opportunities which in turn predicted start-up intentions and activity.

Alternative modes of entrepreneurial opportunity exploitation : the case on inter-organizational project

While entrepreneurship research has taken firm formation to be the predominant mode of opportunity exploitation, entrepreneurship can take place through many other types of organizational arrangements. In the present article, we consider one such alternative arrangement, namely the formation of inter-organizational projects (IOPs). We propose a multi-level contingency model that suggests that uncertainty both at the level of the firm and at the level of the environment makes the exploitation of opportunities through IOPs more likely. The model is tested by telephone survey data collected amongst a panel of 1725 SMEs and longitudinal industry data. Our findings provide strong support for the industry-level part of the model, but interestingly, only partial support for the firm level part of the model. This indicates that the effects of uncertainty need to be dissected into different levels of analysis to understand the conditions under which alternative modes of opportunity exploitation can be a prominent entrepreneurial alternative to new firm formation.

Killing our darling: why we need to let go of the entrepreneurial opportunity construct

We support Shane and Venkataraman’s (2000) basic idea of an “entrepreneurship nexus” where characteristics of the actor as well as those of the “opportunity” they work on influence action and outcomes in the creation of new economic activities. However, a review of the literature reveals that minimal progress has been made on the core issues pertaining to the nexus idea. We argue that this is rooted in fundamental and insurmountable problems with the “opportunity” construct itself, and demonstrate the state of confusion in the literature caused by inconsistent use of the construct within and across works and authors. As an alternative, we suggest the admittedly subjective notion of New Venture as a more workable alternative. We provide a comprehensive definition and explanation of this construct, and take steps towards improved conceptualization and operationalization of its subdimensions. With some further work on these conceptualizations and operationalizations it will be possible to implement a comprehensive research program that can finally deliver on the promise outlined by Shane and Venkataraman (2000).

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.

Finding our way to the future : directions for a city of opportunity

This Australian case study of futures methodologies in local government explores the development and implementation of the Logan 2026 City Directions project. As an innovative approach to strategic planning, and forming the city visioning umbrella for the Strategic Planning and Performance Management Framework of Council, Logan 2026 City Directions has facilitated greater engagement with the community and represents an opportunity for Council to explore and build on the organisation's foresight capacity and to enhance internal communications within the organisation. One significant by-product has been ongoing dialogue and actions of the workshop groups in Council seeking to address such issues as climate change.

Insect odour perception: recognition of odour components by flower foraging moths

Odours emitted by flowers are complex blends of volatile compounds. These odours are learnt by flower-visiting insect species, improving their recognition of rewarding flowers and thus foraging efficiency. We investigated the flexibility of floral odour learning by testing whether adult moths recognize single compounds common to flowers on which they forage. Dual choice preference tests on Helicoverpa armigera moths allowed free flying moths to forage on one of three flower species; Argyranthemum frutescens (federation daisy), Cajanus cajan (pigeonpea) or Nicotiana tabacum (tobacco). Results showed that, (i) a benzenoid (phenylacetaldehyde) and a monoterpene (linalool) were subsequently recognized after visits to flowers that emitted these volatile constituents, (ii) in a preference test, other monoterpenes in the flowers' odour did not affect the moths' ability to recognize the monoterpene linalool and (iii) relative preferences for two volatiles changed after foraging experience on a single flower species that emitted both volatiles. The importance of using free flying insects and real flowers to understand the mechanisms involved in floral odour learning in nature are discussed in the context of our findings.

Vision-based place recognition : how low can you go?

In this paper we use the algorithm SeqSLAM to address the question, how little and what quality of visual information is needed to localize along a familiar route? We conduct a comprehensive investigation of place recognition performance on seven datasets while varying image resolution (primarily 1 to 512 pixel images), pixel bit depth, field of view, motion blur, image compression and matching sequence length. Results confirm that place recognition using single images or short image sequences is poor, but improves to match or exceed current benchmarks as the matching sequence length increases. We then present place recognition results from two experiments where low-quality imagery is directly caused by sensor limitations; in one, place recognition is achieved along an unlit mountain road by using noisy, long-exposure blurred images, and in the other, two single pixel light sensors are used to localize in an indoor environment. We also show failure modes caused by pose variance and sequence aliasing, and discuss ways in which they may be overcome. By showing how place recognition along a route is feasible even with severely degraded image sequences, we hope to provoke a re-examination of how we develop and test future localization and mapping systems.

Feature-domain super-resolution for iris recognition

Uncooperative iris identification systems at a distance suffer from poor resolution of the acquired iris images, which significantly degrades iris recognition performance. Super-resolution techniques have been employed to enhance the resolution of iris images and improve the recognition performance. However, most existing super-resolution approaches proposed for the iris biometric super-resolve pixel intensity values, rather than the actual features used for recognition. This paper thoroughly investigates transferring super-resolution of iris images from the intensity domain to the feature domain. By directly super-resolving only the features essential for recognition, and by incorporating domain specific information from iris models, improved recognition performance compared to pixel domain super-resolution can be achieved. A framework for applying super-resolution to nonlinear features in the feature-domain is proposed. Based on this framework, a novel feature-domain super-resolution approach for the iris biometric employing 2D Gabor phase-quadrant features is proposed. The approach is shown to outperform its pixel domain counterpart, as well as other feature domain super-resolution approaches and fusion techniques.

Recognition and enforcement of foreign judgments : are the rules appropriate?

The recognition and enforcement of foreign judgments is an aspect of private international law, and concerns situations where a successful party to litigation seeks to rely on a judgment obtained in one court, in a court in another jurisdiction. The most common example where the recognition and enforcement of foreign judgments may arise is where a party who has obtained a favourable judgment in one state or country may seek to recognise and enforce the judgment in another state or country. This occurs because there is no sufficient asset in the state or country where the judgment was rendered to satisfy that judgment. As technological advancements in communications over vast geographical distances have improved exponentially in recent years, there has been an increase in cross-border transactions, as well as litigation arising from these transactions. As a result, the recognition and enforcement of foreign judgments is of increasing importance, since a party who has obtained a judgment in cross-border litigation may wish to recognise and enforce the judgment in another state or country, where the defendant’s assets may be located without having to re-litigate substantive issues that have already been resolved in another court. The purpose of the study is to examine whether the current state of laws for the recognition and enforcement of foreign judgments in Australia, the United States and the European Community are in line with modern-commercial needs. The study is conducted by weighing two competing objectives between the notion of finality of litigation, which encourages courts to recognise and enforce judgments foreign to them, on the one hand, and the adequacy of protection to safeguard the recognition and enforcement proceedings, so that there would be no injustice or unfairness if a foreign judgment is recognised and enforced, on the other. The findings of the study are as follows. In both Australia and the United States, there is a different approach concerning the recognition and enforcement of judgments rendered by courts interstate or in a foreign country. In order to maintain a single and integrated nation, there are constitutional and legislative requirements authorising courts to give conclusive effects to interstate judgments. In contrast, if the recognition and enforcement actions involve judgments rendered by a foreign country’s court, an Australian or a United States court will not recognise and enforce the foreign judgment unless the judgment has satisfied a number of requirements and does not fall under any of the exceptions to justify its non-recognition and non-enforcement. In the European Community, the Brussels I Regulation which governs the recognition and enforcement of judgments among European Union Member States has created a scheme, whereby there is only a minimal requirement that needs to be satisfied for the purposes of recognition and enforcement. Moreover, a judgment that is rendered by a Member State and based on any of the jurisdictional bases set forth in the Brussels I Regulation is entitled to be recognised and enforced in another Member State without further review of its underlying jurisdictional basis. However, there are concerns as to the adequacy of protection available under the Brussels I Regulation to safeguard the judgment-enforcing Member States, as well as those against whom recognition or enforcement is sought. This dissertation concludes by making two recommendations aimed at improving the means by which foreign judgments are recognised and enforced in the selected jurisdictions. The first is for the law in both Australia and the United States to undergo reform, including: adopting the real and substantial connection test as the new jurisdictional basis for the purposes of recognition and enforcement; liberalising the existing defences to safeguard the application of the real and substantial connection test; extending the application of the Foreign Judgments Act 1991 (Cth) in Australia to include at least its important trading partners; and implementing a federal statutory scheme in the United States to govern the recognition and enforcement of foreign judgments. The second recommendation is to introduce a convention on jurisdiction and the recognition and enforcement of foreign judgments. The convention will be a convention double, which provides uniform standards for the rules of jurisdiction a court in a contracting state must exercise when rendering a judgment and a set of provisions for the recognition and enforcement of resulting judgments.