Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

The use of visual analogue scales to assess motivation to eat in human subjects: a review of their reliability and validity with an evaluation of new hand-held computerized stsytems for temporal tracking of appetite ratings.

This present paper reviews the reliability and validity of visual analogue scales (VAS) in terms of (1) their ability to predict feeding behaviour, (2) their sensitivity to experimental manipulations, and (3) their reproducibility. VAS correlate with, but do not reliably predict, energy intake to the extent that they could be used as a proxy of energy intake. They do predict meal initiation in subjects eating their normal diets in their normal environment. Under laboratory conditions, subjectively rated motivation to eat using VAS is sensitive to experimental manipulations and has been found to be reproducible in relation to those experimental regimens. Other work has found them not to be reproducible in relation to repeated protocols. On balance, it would appear, in as much as it is possible to quantify, that VAS exhibit a good degree of within-subject reliability and validity in that they predict with reasonable certainty, meal initiation and amount eaten, and are sensitive to experimental manipulations. This reliability and validity appears more pronounced under the controlled (but more arti®cial) conditions of the laboratory where the signal : noise ratio in experiments appears to be elevated relative to real life. It appears that VAS are best used in within-subject, repeated-measures designs where the effect of different treatments can be compared under similar circumstances. They are best used in conjunction with other measures (e.g. feeding behaviour, changes in plasma metabolites) rather than as proxies for these variables. New hand-held electronic appetite rating systems (EARS) have been developed to increase reliability of data capture and decrease investigator workload. Recent studies have compared these with traditional pen and paper (P&P) VAS. The EARS have been found to be sensitive to experimental manipulations and reproducible relative to P&P. However, subjects appear to exhibit a signi®cantly more constrained use of the scale when using the EARS relative to the P&P. For this reason it is recommended that the two techniques are not used interchangeably

The dynamic processes of visual, corporate, and organisational identity : an exploratory study

The purpose of this study is to contribute to the cross-disciplinary body of literature of identity and organisational culture. This study empirically investigated the Hatch and Schultz (2002) Organisational Identity Dynamics (OID) model to look at linkages between identity, image, and organisational culture. This study used processes defined in the OID model as a theoretical frame by which to understand the relationships between actual and espoused identity manifestations across visual identity, corporate identity, and organisational identity. The linking processes of impressing, mirroring, reflecting, and expressing were discussed at three unique levels in the organisation. The overarching research question of How does the organisational identity dynamics process manifest itself in practice at different levels within an organisation? was used as a means of providing empirical understanding to the previously theoretical OID model. Case study analysis was utilised to provide exploratory data across the organisational groups of: Level A - Senior Marketing and Corporate Communications Management, Level B - Marketing and Corporate Communications Staff, and Level C - Non-Marketing Managers and Employees. Data was collected via 15 in-depth interviews with documentary analysis used as a supporting mechanism to provide triangulation in analysis. Data was analysed against the impressing, mirroring, reflecting, and expressing constructs with specific criteria developed from literature to provide a detailed analysis of each process. Conclusions revealed marked differences in the ways in which OID processes occurred across different levels with implications for the ways in which VI, CI, and OI interact to develop holistic identity across organisational levels. Implications for theory detail the need to understand and utilise cultural understanding in identity programs as well as the value in developing identity communications which represent an actual rather than an espoused position.

Generalising across borders : policy and the limits of educational science.

AERA Distinguished Lecture, Annual Meetings of the American Educational Research Association, New Orleans, 8 April 2011. How well does educational policy, innovation and science cross borders? What are the parameters of a generalisable cultural science of education? What constitutes a principled policy 'borrowing'?

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Gap analysis of intrusion detection in smart grids

Given the recent emergence of the smart grid and smart grid related technologies, their security is a prime concern. Intrusion detection provides a second line of defense. However, conventional intrusion detection systems (IDSs) are unable to adequately address the unique requirements of the smart grid. This paper presents a gap analysis of contemporary IDSs from a smart grid perspective. This paper highlights the lack of adequate intrusion detection within the smart grid and discusses the limitations of current IDSs approaches. The gap analysis identifies current IDSs as being unsuited to smart grid application without significant changes to address smart grid specific requirements.

The limits of competition : reasserting a role for consumer protection and fair trading regulation in competitive markets

In this paper we advocate for the continued need for consumer protection and fair trading regulation, even in competitive markets. For the purposes of this paper a ‘competitive market’ is defined as one that has low barriers to entry and exit, with homogenous products and services and numerous suppliers. Whilst competition is an important tool for providing consumer benefits, it will not be sufficient to protect at least some consumers, particularly vulnerable, low income consumers. For this reason, we argue, setting competition as the ‘end goal’ and assuming that consumer protection and consumer benefits will always follow, is a flawed regulatory approach. The ‘end goal’ should surely be consumer protection and fair markets, and a combination of competition law and consumer protection law should be applied in order to achieve those goals.

Field-of-view, detection range, and false alarm trade-offs in vision-based aircraft detection

This paper presents a survey of previously presented vision based aircraft detection flight test, and then presents new flight test results examining the impact of camera field-of view choice on the detection range and false alarm rate characteristics of a vision-based aircraft detection technique. Using data collected from approaching aircraft, we examine the impact of camera fieldof-view choice and confirm that, when aiming for similar levels of detection confidence, an improvement in detection range can be obtained by choosing a smaller effective field-of-view (in terms of degrees per pixel).

Visual sensitivity loss in the central thirty degrees of visual field is associated with diabetic peripheral neuropathy

Aims/hypothesis: Impaired central vision has been shown to predict diabetic peripheral neuropathy (DPN). Several studies have demonstrated diffuse retinal neurodegenerative changes in diabetic patients prior to retinopathy development, raising the prospect that non-central vision may also be compromised by primary neural damage. We hypothesise that type 2 diabetic patients with DPN exhibit visual sensitivity loss in a distinctive pattern across the visual field, compared with a control group of type 2 diabetic patients without DPN. Methods: Increment light sensitivity was measured by standard perimetry in the central 30 degree of visual field for two age-matched groups of type 2 diabetic patients, with and without neuropathy (n=40/30). Neuropathy status was assigned using the neuropathy disability score. Mean visual sensitivity values were calculated globally, for each quadrant and for three eccentricities (0-10 degree , 11-20 degree and 21-30 degree ). Data were analysed using a generalised additive mixed model (GAMM). Results: Global and quadrant between-group visual sensitivity mean differences were marginally but consistently lower (by about 1 dB) in the neuropathy cohort compared with controls. Between-group mean differences increased from 0.36 to 1.81 dB with increasing eccentricity. GAMM analysis, after adjustment for age, showed these differences to be significant beyond 15 degree eccentricity and monotonically increasing. Retinopathy levels and disease duration were not significant factors within the model (p=0.90). Conclusions/interpretation: Visual sensitivity reduces disproportionately with increasing eccentricity in type 2 diabetic patients with peripheral neuropathy. This sensitivity reduction within the central 30 degree of visual field may be indicative of more consequential loss in the far periphery.

Automatic region-of-interest detection and prioritisation for visually optimised coding of low bit rate videos

The increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.

Comparison of antigen detection and quantitative PCR in the detection of chlamydial infection in koalas (Phascolarctos cinereus)

The gold standard method for detecting chlamydial infection in domestic and wild animals is PCR, but the technique is not suited to testing animals in the field when a rapid diagnosis is frequently required. The objective of this study was to compare the results of a commercially available enzyme immunoassay test for Chlamydia against a quantitative Chlamydia pecorum-specific PCR performed on swabs collected from the conjunctival sac, nasal cavity and urogenital sinuses of naturally infected koalas (Phascolarctos cinereus). The level of agreement for positive results between the two assays was low (43.2%). The immunoassay detection cut-off was determined as approximately 400 C. pecorum copies, indicating that the test was sufficiently sensitive to be used for the rapid diagnosis of active chlamydial infections.

Solving inherent problems of anomaly detection by cooperation

Anomaly detection compensates shortcomings of signature-based detection such as protecting against Zero-Day exploits. However, Anomaly Detection can be resource-intensive and is plagued by a high false-positive rate. In this work, we address these problems by presenting a Cooperative Intrusion Detection approach for the AIS, the Artificial Immune System, as an example for an anomaly detection approach. In particular we show, how the cooperative approach reduces the false-positive rate of the detection and how the overall detection process can be organized to account for the resource constraints of the participating devices. Evaluations are carried out with the novel network simulation environment NeSSi as well as formally with an extension to the epidemic spread model SIR

Does experience with one type of two-wheeler affect behaviours and attitudes to other types?

Failure to give way by motor vehicles is a factor in many collisions with both powered and unpowered two wheelers (TWs). Motor vehicle drivers often report that they did not see the TW, but research has shown that motor vehicle drivers who have experience riding a motorcycle are less likely to fail to detect motorcycles. The research reported here examines whether this phenomenon extends to detection of bicycles and whether car drivers who have experience with one mode of TW show improved detection of the other mode. A driving simulator study was conducted in an Australian urban setting which incorporated some of the most common car-TW crash scenarios. Participants with car-only, car plus motorcycle, car plus bicycle, and car plus bicycle plus motorcycle experience operated a car simulator. Their interactions with both types of TWs were measured in terms of visual detection, lateral distance and speed when approaching and passing. The effects of different levels of colour and lighting of the TWs on driver responses were also examined. The attitudes of participants towards TWs were measured in a questionnaire.