914 resultados para CENTERBAND-ONLY DETECTION
Resumo:
Abandoned object detection (AOD) systems are required to run in high traffic situations, with high levels of occlusion. Systems rely on background segmentation techniques to locate abandoned objects, by detecting areas of motion that have stopped. This is often achieved by using a medium term motion detection routine to detect long term changes in the background. When AOD systems are integrated into person tracking system, this often results in two separate motion detectors being used to handle the different requirements. We propose a motion detection system that is capable of detecting medium term motion as well as regular motion. Multiple layers of medium term (static) motion can be detected and segmented. We demonstrate the performance of this motion detection system and as part of an abandoned object detection system.
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Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.
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This chapter looks at issues of non-stationarity in determining when a transient has occurred and when it is possible to fit a linear model to a non-linear response. The first issue is associated with the detection of loss of damping of power system modes. When some control device such as an SVC fails, the operator needs to know whether the damping of key power system oscillation modes has deteriorated significantly. This question is posed here as an alarm detection problem rather than an identification problem to get a fast detection of a change. The second issue concerns when a significant disturbance has occurred and the operator is seeking to characterize the system oscillation. The disturbance initially is large giving a nonlinear response; this then decays and can then be smaller than the noise level ofnormal customer load changes. The difficulty is one of determining when a linear response can be reliably identified between the non-linear phase and the large noise phase of thesignal. The solution proposed in this chapter uses “Time-Frequency” analysis tools to assistthe extraction of the linear model.
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Purpose: This two-part research project was undertaken as part of the planning process by Queensland Health (QH), Cancer Screening Services Unit (CSSU), Queensland Bowel Cancer Screening Program (QBCSP), in partnership with the National Bowel Cancer Screening Program (NBCSP), to prepare for the implementation of the NBCSP in public sector colonoscopy services in QLD in late 2006. There was no prior information available on the quality of colonoscopy services in Queensland (QLD) and no prior studies that assessed the quality of colonoscopy training in Australia. Furthermore, the NBCSP was introduced without extra funding for colonoscopy service improvement or provision for increases in colonoscopic capacity resulting from the introduction of the NBCSP. The main purpose of the research was to record baseline data on colonoscopy referral and practice in QLD and current training in colonoscopy Australia-wide. It was undertaken from a quality improvement perspective. Implementation of the NBCSP requires that all aspects of the screening pathway, in particular colonoscopy services for the assessment of positive Faecal Occult Blood Tests (FOBTs), will be effective, efficient, equitable and evidence-based. This study examined two important aspects of the continuous quality improvement framework for the NBCSP as they relate to colonoscopy services: (1) evidence-based practice, and (2) quality of colonoscopy training. The Principal Investigator was employed as Senior Project Officer (Training) in the QBCSP during the conduct of this research project. Recommendations from this research have been used to inform the development and implementation of quality improvement initiatives for provision of colonoscopy in the NBCSP, its QLD counterpart the QBCSP and colonoscopy services in QLD, in general. Methods – Part 1 Chart audit of evidence-based practice: The research was undertaken in two parts from 2005-2007. The first part of this research comprised a retrospective chart audit of 1484 colonoscopy records (some 13% of all colonoscopies conducted in public sector facilities in the year 2005) in three QLD colonoscopy services. Whilst some 70% of colonoscopies are currently conducted in the private sector, only public sector colonoscopy facilities provided colonoscopies under the NBCSP. The aim of this study was to compare colonoscopy referral and practice with explicit criteria derived from the National Health & Medical Research Council (NHMRC) (1999) Clinical Practice Guidelines for the Prevention, Early Detection and Management of Colorectal Cancer, and describe the nature of variance with the guidelines. Symptomatic presentations were the most common indication for colonoscopy (60.9%). These comprised per rectal bleeding (31.0%), change of bowel habit (22.1%), abdominal pain (19.6%), iron deficiency anaemia (16.2%), inflammatory bowel disease (8.9%) and other symptoms (11.4%). Surveillance and follow-up colonoscopies accounted for approximately one-third of the remaining colonoscopy workload across sites. Gastroenterologists (GEs) performed relatively more colonoscopies per annum (59.9%) compared to general surgeons (GS) (24.1%), colorectal surgeons (CRS) (9.4%) and general physicians (GPs) (6.5%). Guideline compliance varied with the designation of the colonoscopist. Compliance was lower for CRS (62.9%) compared to GPs (76.0%), GEs (75.0%), GSs (70.9%, p<0.05). Compliance with guideline recommendations for colonoscopic surveillance for family history of colorectal cancer (23.9%), polyps (37.0%) and a past history of bowel cancer (42.7%), was by comparison significantly lower than for symptomatic presentations (94.4%), (p<0.001). Variation with guideline recommendations occurred more frequently for polyp surveillance (earlier than guidelines recommend, 47.9%) and follow-up for past history of bowel cancer (later than recommended, 61.7%, p<0.001). Bowel cancer cases detected at colonoscopy comprised 3.6% of all audited colonoscopies. Incomplete colonoscopies occurred in 4.3% of audited colonoscopies and were more common among women (76.6%). For all colonoscopies audited, the rate of incomplete colonoscopies for GEs was 1.6% (CI 0.9-2.6), GPs 2.0% (CI 0.6-7.2), GS 7.0% (CI 4.8-10.1) and CRS 16.4% (CI 11.2-23.5). 18.6% (n=55) of patients with a documented family history of bowel cancer had colonoscopy performed against guidelines recommendations (for general (category 1) population risk, for reasons of patient request or family history of polyps, rather than for high risk status for colorectal cancer). In general, family history was inadequately documented and subsequently applied to colonoscopy referral and practice. Methods - Part 2 Surveys of quality of colonoscopy training: The second part of the research consisted of Australia-wide anonymous, self-completed surveys of colonoscopy trainers and their trainees to ascertain their opinions on the current apprenticeship model of colonoscopy in Australia and to identify any training needs. Overall, 127 surveys were received from colonoscopy trainers (estimated response rate 30.2%). Approximately 50% of trainers agreed and 27% disagreed that current numbers of training places were adequate to maintain a skilled colonoscopy workforce in preparation for the NBCSP. Approximately 70% of trainers also supported UK-style colonoscopy training within dedicated accredited training centres using a variety of training approaches including simulation. A collaborative approach with the private sector was seen as beneficial by 65% of trainers. Non-gastroenterologists (non-GEs) were more likely than GEs to be of the opinion that simulators are beneficial for colonoscopy training (χ2-test = 5.55, P = 0.026). Approximately 60% of trainers considered that the current requirements for recognition of training in colonoscopy could be insufficient for trainees to gain competence and 80% of those indicated that ≥ 200 colonoscopies were needed. GEs (73.4%) were more likely than non-GEs (36.2%) to be of the opinion that the Conjoint Committee standard is insufficient to gain competence in colonoscopy (χ2-test = 16.97, P = 0.0001). The majority of trainers did not support training either nurses (73%) or GPs in colonoscopy (71%). Only 81 (estimated response rate 17.9%) surveys were received from GS trainees (72.1%), GE trainees (26.3%) and GP trainees (1.2%). The majority were males (75.9%), with a median age 32 years and who had trained in New South Wales (41.0%) or Victoria (30%). Overall, two-thirds (60.8%) of trainees indicated that they deemed the Conjoint Committee standard sufficient to gain competency in colonoscopy. Between specialties, 75.4% of GS trainees indicated that the Conjoint Committee standard for recognition of colonoscopy was sufficient to gain competence in colonoscopy compared to only 38.5% of GE trainees. Measures of competency assessed and recorded by trainees in logbooks centred mainly on caecal intubation (94.7-100%), complications (78.9-100%) and withdrawal time (51-76.2%). Trainees described limited access to colonoscopy training lists due to the time inefficiency of the apprenticeship model and perceived monopolisation of these by GEs and their trainees. Improvements to the current training model suggested by trainees included: more use of simulation, training tools, a United Kingdom (UK)-style training course, concentration on quality indicators, increased access to training lists, accreditation of trainers and interdisciplinary colonoscopy training. Implications for the NBCSP/QBCSP: The introduction of the NBCSP/QBCSP necessitates higher quality colonoscopy services if it is to achieve its ultimate goal of decreasing the incidence of morbidity and mortality associated with bowel cancer in Australia. This will be achieved under a new paradigm for colonoscopy training and implementation of evidence-based practice across the screening pathway and specifically targeting areas highlighted in this thesis. Recommendations for improvement of NBCSP/QBCSP effectiveness and efficiency include the following: 1. Implementation of NBCSP and QBCSP health promotion activities that target men, in particular, to increase FOBT screening uptake. 2. Improved colonoscopy training for trainees and refresher courses or retraining for existing proceduralists to improve completion rates (especially for female NBCSP/QBCSP participants), and polyp and adenoma detection and removal, including newer techniques to detect flat and depressed lesions. 3. Introduction of colonoscopy training initiatives for trainees that are aligned with NBCSP/QBCSP colonoscopy quality indicators, including measurement of training outcomes using objective quality indicators such as caecal intubation, withdrawal time, and adenoma detection rate. 4. Introduction of standardised, interdisciplinary colonoscopy training to reduce apparent differences between specialties with regard to compliance with guideline recommendations, completion rates, and quality of polypectomy. 5. Improved quality of colonoscopy training by adoption of a UK-style training program with centres of excellence, incorporating newer, more objective assessment methods, use of a variety of training tools such as simulation and rotations of trainees between metropolitan, rural, and public and private sector training facilities. 6. Incorporation of NHMRC guidelines into colonoscopy information systems to improve documentation, provide guideline recommendations at the point of care, use of gastroenterology nurse coordinators to facilitate compliance with guidelines and provision of guideline-based colonoscopy referral letters for GPs. 7. Provision of information and education about the NBCSP/QBCSP, bowel cancer risk factors, including family history and polyp surveillance guidelines, for participants, GPs and proceduralists. 8. Improved referral of NBCSP/QBCSP participants found to have a high-risk family history of bowel cancer to appropriate genetics services.
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An Approach with Vertical Guidance (APV) is an instrument approach procedure which provides horizontal and vertical guidance to a pilot on approach to landing in reduced visibility conditions. APV approaches can greatly reduce the safety risk to general aviation by improving the pilot’s situational awareness. In particular the incidence of Controlled Flight Into Terrain (CFIT) which has occurred in a number of fatal air crashes in general aviation over the past decade in Australia, can be reduced. APV approaches can also improve general aviation operations. If implemented at Australian airports, APV approach procedures are expected to bring a cost saving of millions of dollars to the economy due to fewer missed approaches, diversions and an increased safety benefit. The provision of accurate horizontal and vertical guidance is achievable using the Global Positioning System (GPS). Because aviation is a safety of life application, an aviation-certified GPS receiver must have integrity monitoring or augmentation to ensure that its navigation solution can be trusted. However, the difficulty with the current GPS satellite constellation alone meeting APV integrity requirements, the susceptibility of GPS to jamming or interference and the potential shortcomings of proposed augmentation solutions for Australia such as the Ground-based Regional Augmentation System (GRAS) justifies the investigation of Aircraft Based Augmentation Systems (ABAS) as an alternative integrity solution for general aviation. ABAS augments GPS with other sensors at the aircraft to help it meet the integrity requirements. Typical ABAS designs assume high quality inertial sensors to provide an accurate reference trajectory for Kalman filters. Unfortunately high-quality inertial sensors are too expensive for general aviation. In contrast to these approaches the purpose of this research is to investigate fusing GPS with lower-cost Micro-Electro-Mechanical System (MEMS) Inertial Measurement Units (IMU) and a mathematical model of aircraft dynamics, referred to as an Aircraft Dynamic Model (ADM) in this thesis. Using a model of aircraft dynamics in navigation systems has been studied before in the available literature and shown to be useful particularly for aiding inertial coasting or attitude determination. In contrast to these applications, this thesis investigates its use in ABAS. This thesis presents an ABAS architecture concept which makes use of a MEMS IMU and ADM, named the General Aviation GPS Integrity System (GAGIS) for convenience. GAGIS includes a GPS, MEMS IMU, ADM, a bank of Extended Kalman Filters (EKF) and uses the Normalized Solution Separation (NSS) method for fault detection. The GPS, IMU and ADM information is fused together in a tightly-coupled configuration, with frequent GPS updates applied to correct the IMU and ADM. The use of both IMU and ADM allows for a number of different possible configurations. Three are investigated in this thesis; a GPS-IMU EKF, a GPS-ADM EKF and a GPS-IMU-ADM EKF. The integrity monitoring performance of the GPS-IMU EKF, GPS-ADM EKF and GPS-IMU-ADM EKF architectures are compared against each other and against a stand-alone GPS architecture in a series of computer simulation tests of an APV approach. Typical GPS, IMU, ADM and environmental errors are simulated. The simulation results show the GPS integrity monitoring performance achievable by augmenting GPS with an ADM and low-cost IMU for a general aviation aircraft on an APV approach. A contribution to research is made in determining whether a low-cost IMU or ADM can provide improved integrity monitoring performance over stand-alone GPS. It is found that a reduction of approximately 50% in protection levels is possible using the GPS-IMU EKF or GPS-ADM EKF as well as faster detection of a slowly growing ramp fault on a GPS pseudorange measurement. A second contribution is made in determining how augmenting GPS with an ADM compares to using a low-cost IMU. By comparing the results for the GPS-ADM EKF against the GPS-IMU EKF it is found that protection levels for the GPS-ADM EKF were only approximately 2% higher. This indicates that the GPS-ADM EKF may potentially replace the GPS-IMU EKF for integrity monitoring should the IMU ever fail. In this way the ADM may contribute to the navigation system robustness and redundancy. To investigate this further, a third contribution is made in determining whether or not the ADM can function as an IMU replacement to improve navigation system redundancy by investigating the case of three IMU accelerometers failing. It is found that the failed IMU measurements may be supplemented by the ADM and adequate integrity monitoring performance achieved. Besides treating the IMU and ADM separately as in the GPS-IMU EKF and GPS-ADM EKF, a fourth contribution is made in investigating the possibility of fusing the IMU and ADM information together to achieve greater performance than either alone. This is investigated using the GPS-IMU-ADM EKF. It is found that the GPS-IMU-ADM EKF can achieve protection levels approximately 3% lower in the horizontal and 6% lower in the vertical than a GPS-IMU EKF. However this small improvement may not justify the complexity of fusing the IMU with an ADM in practical systems. Affordable ABAS in general aviation may enhance existing GPS-only fault detection solutions or help overcome any outages in augmentation systems such as the Ground-based Regional Augmentation System (GRAS). Countries such as Australia which currently do not have an augmentation solution for general aviation could especially benefit from the economic savings and safety benefits of satellite navigation-based APV approaches.
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Information fusion in biometrics has received considerable attention. The architecture proposed here is based on the sequential integration of multi-instance and multi-sample fusion schemes. This method is analytically shown to improve the performance and allow a controlled trade-off between false alarms and false rejects when the classifier decisions are statistically independent. Equations developed for detection error rates are experimentally evaluated by considering the proposed architecture for text dependent speaker verification using HMM based digit dependent speaker models. The tuning of parameters, n classifiers and m attempts/samples, is investigated and the resultant detection error trade-off performance is evaluated on individual digits. Results show that performance improvement can be achieved even for weaker classifiers (FRR-19.6%, FAR-16.7%). The architectures investigated apply to speaker verification from spoken digit strings such as credit card numbers in telephone or VOIP or internet based applications.
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Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.
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ERP systems generally implement controls to prevent certain common kinds of fraud. In addition however, there is an imperative need for detection of more sophisticated patterns of fraudulent activity as evidenced by the legal requirement for company audits and the common incidence of fraud. This paper describes the design and implementation of a framework for detecting patterns of fraudulent activity in ERP systems. We include the description of six fraud scenarios and the process of specifying and detecting the occurrence of those scenarios in ERP user log data using the prototype software which we have developed. The test results for detecting these scenarios in log data have been verified and confirm the success of our approach which can be generalized to ERP systems in general.
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Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (as opposed to radar). This paper describes the development and evaluation of a vision-based collision detection algorithm suitable for fixed-wing aerial robotics. The system was evaluated using highly realistic vision data of the moments leading up to a collision. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We make use of the enormous potential of graphic processing units to achieve processing rates of 30Hz (for images of size 1024-by- 768). Currently, integration in the final platform is under way.
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Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of vision sensors (as opposed to radar and TCAS). This paper describes the development and evaluation of a real-time vision-based collision detection system suitable for fixed-wing aerial robotics. Using two fixed-wing UAVs to recreate various collision-course scenarios, we were able to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. This type of image data is extremely scarce and was invaluable in evaluating the detection performance of two candidate target detection approaches. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We overcame the challenge of achieving real-time computational speeds by exploiting the parallel processing architectures of graphics processing units found on commercially-off-the-shelf graphics devices. Our chosen GPU device suitable for integration onto UAV platforms can be expected to handle real-time processing of 1024 by 768 pixel image frames at a rate of approximately 30Hz. Flight trials using manned Cessna aircraft where all processing is performed onboard will be conducted in the near future, followed by further experiments with fully autonomous UAV platforms.
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Robust texture recognition in underwater image sequences for marine pest population control such as Crown-Of-Thorns Starfish (COTS) is a relatively unexplored area of research. Typically, humans count COTS by laboriously processing individual images taken during surveys. Being able to autonomously collect and process images of reef habitat and segment out the various marine biota holds the promise of allowing researchers to gain a greater understanding of the marine ecosystem and evaluate the impact of different environmental variables. This research applies and extends the use of Local Binary Patterns (LBP) as a method for texture-based identification of COTS from survey images. The performance and accuracy of the algorithms are evaluated on a image data set taken on the Great Barrier Reef.
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Motion has been examined in biology to be a critical component for obstacle avoidance and navigation. In particular, optical flow is a powerful motion cue that has been exploited in many biological systems for survival. In this paper, we investigate an obstacle detection system that uses optical flow to obtain range information to objects. Our experimental results demonstrate that optical flow is capable of providing good obstacle information but has obvious failure modes. We acknowledge that our optical flow system has certain disadvantages and cannot be solely used for navigation. Instead, we believe that optical flow is a critical visual subsystem used when moving at reason- able speeds. When combined with other visual subsystems, considerable synergy can result.
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Simultaneous Localization And Mapping (SLAM) is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision only approaches. This paper presents a method for generating approximate rotational and translation velocity information from a single vehicle-mounted consumer camera, without the computationally expensive process of tracking landmarks. The method is tested by employing it to provide the odometric and visual information for the RatSLAM system while mapping a complex suburban road network. RatSLAM generates a coherent map of the environment during an 18 km long trip through suburban traffic at speeds of up to 60 km/hr. This result demonstrates the potential of ground based vision-only SLAM using low cost sensing and computational hardware.
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Secret-sharing schemes describe methods to securely share a secret among a group of participants. A properly constructed secret-sharing scheme guarantees that the share belonging to one participant does not reveal anything about the shares of others or even the secret itself. Besides the obvious feature which is to distribute a secret, secret-sharing schemes have also been used in secure multi-party computations and redundant residue number systems for error correction codes. In this paper, we propose that the secret-sharing scheme be used as a primitive in a Network-based Intrusion Detection System (NIDS) to detect attacks in encrypted networks. Encrypted networks such as Virtual Private Networks (VPNs) fully encrypt network traffic which can include both malicious and non-malicious traffic. Traditional NIDS cannot monitor encrypted traffic. Our work uses a combination of Shamir's secret-sharing scheme and randomised network proxies to enable a traditional NIDS to function normally in a VPN environment. In this paper, we introduce a novel protocol that utilises a secret-sharing scheme to detect attacks in encrypted networks.
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Non-driving related cognitive load and variations of emotional state may impact a driver’s capability to control a vehicle and introduces driving errors. Availability of reliable cognitive load and emotion detection in drivers would benefit the design of active safety systems and other intelligent in-vehicle interfaces. In this study, speech produced by 68 subjects while driving in urban areas is analyzed. A particular focus is on speech production differences in two secondary cognitive tasks, interactions with a co-driver and calls to automated spoken dialog systems (SDS), and two emotional states during the SDS interactions - neutral/negative. A number of speech parameters are found to vary across the cognitive/emotion classes. Suitability of selected cepstral- and production-based features for automatic cognitive task/emotion classification is investigated. A fusion of GMM/SVM classifiers yields an accuracy of 94.3% in cognitive task and 81.3% in emotion classification.