Multiple camera management using wide baseline matching

Camera calibration information is required in order for multiple camera networks to deliver more than the sum of many single camera systems. Methods exist for manually calibrating cameras with high accuracy. Manually calibrating networks with many cameras is, however, time consuming, expensive and impractical for networks that undergo frequent change. For this reason, automatic calibration techniques have been vigorously researched in recent years. Fully automatic calibration methods depend on the ability to automatically find point correspondences between overlapping views. In typical camera networks, cameras are placed far apart to maximise coverage. This is referred to as a wide base-line scenario. Finding sufficient correspondences for camera calibration in wide base-line scenarios presents a significant challenge. This thesis focuses on developing more effective and efficient techniques for finding correspondences in uncalibrated, wide baseline, multiple-camera scenarios. The project consists of two major areas of work. The first is the development of more effective and efficient view covariant local feature extractors. The second area involves finding methods to extract scene information using the information contained in a limited set of matched affine features. Several novel affine adaptation techniques for salient features have been developed. A method is presented for efficiently computing the discrete scale space primal sketch of local image features. A scale selection method was implemented that makes use of the primal sketch. The primal sketch-based scale selection method has several advantages over the existing methods. It allows greater freedom in how the scale space is sampled, enables more accurate scale selection, is more effective at combining different functions for spatial position and scale selection, and leads to greater computational efficiency. Existing affine adaptation methods make use of the second moment matrix to estimate the local affine shape of local image features. In this thesis, it is shown that the Hessian matrix can be used in a similar way to estimate local feature shape. The Hessian matrix is effective for estimating the shape of blob-like structures, but is less effective for corner structures. It is simpler to compute than the second moment matrix, leading to a significant reduction in computational cost. A wide baseline dense correspondence extraction system, called WiDense, is presented in this thesis. It allows the extraction of large numbers of additional accurate correspondences, given only a few initial putative correspondences. It consists of the following algorithms: An affine region alignment algorithm that ensures accurate alignment between matched features; A method for extracting more matches in the vicinity of a matched pair of affine features, using the alignment information contained in the match; An algorithm for extracting large numbers of highly accurate point correspondences from an aligned pair of feature regions. Experiments show that the correspondences generated by the WiDense system improves the success rate of computing the epipolar geometry of very widely separated views. This new method is successful in many cases where the features produced by the best wide baseline matching algorithms are insufficient for computing the scene geometry.

Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Knowledge management competence for Enterprise System success

This study conceptualizes, operationalises and validates the concept of Knowledge Management Competence as a four-phase multidimensional formative index. Employing survey data from 310 respondents representing 27 organizations using the SAP Enterprise System Financial module, the study results demonstrate a large, significant, positive relationship between Knowledge Management Competence and Enterprise Systems Success (ES-success, as conceived by Gable Sedera and Chan (2008)); suggesting important implications for practice. Strong evidence of the validity of Knowledge Management Competence as conceived and operationalised, too suggests potential from future research evaluating its relationships with possible antecedents and consequences.

Randomised controlled trial of an automated, interactive telephone intervention to improve type 2 diabetes self-management (Telephone-Linked Care Diabetes Project) : study protocol

Background: An estimated 285 million people worldwide have diabetes and its prevalence is predicted to increase to 439 million by 2030. For the year 2010, it is estimated that 3.96 million excess deaths in the age group 20-79 years are attributable to diabetes around the world. Self-management is recognised as an integral part of diabetes care. This paper describes the protocol of a randomised controlled trial of an automated interactive telephone system aiming to improve the uptake and maintenance of essential diabetes self-management behaviours. ---------- Methods/Design: A total of 340 individuals with type 2 diabetes will be randomised, either to the routine care arm, or to the intervention arm in which participants receive the Telephone-Linked Care (TLC) Diabetes program in addition to their routine care. The intervention requires the participants to telephone the TLC Diabetes phone system weekly for 6 months. They receive the study handbook and a glucose meter linked to a data uploading device. The TLC system consists of a computer with software designed to provide monitoring, tailored feedback and education on key aspects of diabetes self-management, based on answers voiced or entered during the current or previous conversations. Data collection is conducted at baseline (Time 1), 6-month follow-up (Time 2), and 12-month follow-up (Time 3). The primary outcomes are glycaemic control (HbA1c) and quality of life (Short Form-36 Health Survey version 2). Secondary outcomes include anthropometric measures, blood pressure, blood lipid profile, psychosocial measures as well as measures of diet, physical activity, blood glucose monitoring, foot care and medication taking. Information on utilisation of healthcare services including hospital admissions, medication use and costs is collected. An economic evaluation is also planned.---------- Discussion: Outcomes will provide evidence concerning the efficacy of a telephone-linked care intervention for self-management of diabetes. Furthermore, the study will provide insight into the potential for more widespread uptake of automated telehealth interventions, globally.

Flight testing of an augmented separation management system providing separation protection during failure of the central communication network

Future air traffic management concepts often involve the proposal of automated separation management algorithms that replaces human air traffic controllers. This paper proposes a new type of automated separation management algorithm (based on the satisficing approach) that utilizes inter-aircraft communication and a track file manager (or bank of Kalman filters) that is capable of resolving conflicts during periods of communication failure. The proposed separation management algorithm is tested in a range of flight scenarios involving during periods of communication failure, in both simulation and flight test (flight tests were conducted as part of the Smart Skies project). The intention of the conducted flight tests was to investigate the benefits of using inter-aircraft communication to provide an extra layer of safety protection in support air traffic management during periods of failure of the communication network. These benefits were confirmed.

Designing a workflow system using coloured petri nets

Traditional workflow systems focus on providing support for the control-flow perspective of a business process, with other aspects such as data management and work distribution receiving markedly less attention. A guide to desirable workflow characteristics is provided by the well-known workflow patterns which are derived from a comprehensive survey of contemporary tools and modelling formalisms. In this paper we describe the approach taken to designing the newYAWL workflow system, an offering that aims to provide comprehensive support for the control-flow, data and resource perspectives based on the workflow patterns. The semantics of the newYAWL workflow language are based on Coloured Petri Nets thus facilitating the direct enactment and analysis of processes described in terms of newYAWL language constructs. As part of this discussion, we explain how the operational semantics for each of the language elements are embodied in the newYAWL system and indicate the facilities required to support them in an operational environment. We also review the experiences associated with developing a complete operational design for an offering of this scale using formal techniques.

Semi-supervised intelligent surveillance system for secure environments

This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

Implementing an employee performance management system in a nonprofit organization

Nonprofit organizations are not exempt from the imperatives of employee attraction, retention, and motivation. As competition for staff, donors, and funding increases, the need to manage employee performance will continue to be a critical human resource management issue. This article outlines a study of the introduction of a performance management system in an Australian nonprofit organization and analyzes its design and implementation. It explores how performance management can be introduced and used effectively within a nonprofit environment to benefit staff and the organization. However, the use of performance management is not without its challenges, and the research also identified initial employee resistance and a resulting initial spike in labor turnover. However, findings indicate that if nonprofit organizations are willing to undertake consultation with staff and ensure that the organization's specific context, values, and mission are reflected in the performance management system, it can be a useful tool for managers and a direct benefit to employees.

Local adjustment and global adaptation of control periods for QoC management of control systems

Linking real-time schedulability directly to the Quality of Control (QoC), the ultimate goal of a control system, a hierarchical feedback QoC management framework with the Fixed Priority (FP) and the Earliest-Deadline-First (EDF) policies as plug-ins is proposed in this paper for real-time control systems with multiple control tasks. It uses a task decomposition model for continuous QoC evaluation even in overload conditions, and then employs heuristic rules to adjust the period of each of the control tasks for QoC improvement. If the total requested workload exceeds the desired value, global adaptation of control periods is triggered for workload maintenance. A sufficient stability condition is derived for a class of control systems with delay and period switching of the heuristic rules. Examples are given to demonstrate the proposed approach.

Loculus : an ontology-based information management framework for the motion picture industry

"How do you film a punch?" This question can be posed by actors, make-up artists, directors and cameramen. Though they can all ask the same question, they are not all seeking the same answer. Within a given domain, based on the roles they play, agents of the domain have different perspectives and they want the answers to their question from their perspective. In this example, an actor wants to know how to act when filming a scene involving a punch. A make-up artist is interested in how to do the make-up of the actor to show bruises that may result from the punch. Likewise, a director wants to know how to direct such a scene and a cameraman is seeking guidance on how best to film such a scene. This role-based difference in perspective is the underpinning of the Loculus framework for information management for the Motion Picture Industry. The Loculus framework exploits the perspective of agent for information extraction and classification within a given domain. The framework uses the positioning of the agent’s role within the domain ontology and its relatedness to other concepts in the ontology to determine the perspective of the agent. Domain ontology had to be developed for the motion picture industry as the domain lacked one. A rule-based relatedness score was developed to calculate the relative relatedness of concepts with the ontology, which were then used in the Loculus system for information exploitation and classification. The evaluation undertaken to date have yielded promising results and have indicated that exploiting perspective can lead to novel methods of information extraction and classifications.