994 resultados para Head tracking
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Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don’t discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.
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Clinical Nutrition for Oncology Patients provides clinicians with the information they need to help cancer survivors and patients make informed choices about their nutrition and improve their short-term and long-term health. This comprehensive resource outlines nutritional management recommendations for care prior to, during, and after treatment and addresses specific nutritional needs and complementary therapies that may be of help to a patient. This book is written by a variety of clinicians who not only care for cancer survivors and their caregivers but are also experts in the field of nutritional oncology.
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The Guide contains the distilled findings from a major, two-year research project to explore those factors considered by industry practitioners to be critical to the successful adoption of ICT, both within their firms and between their firms and their trading partners. In the context of this project Critical Success Factors (CSFs) have been defined as, “Those things that absolutely, positively must be attended to in order to maximise the likelihood of a successful outcome for the stakeholder, defined in the stakeholder’s terms.” The guide includes: o Perceived benefits of ICT use across the head contractors’ sector o Types and levels of ICT used across the sector o Self-assessment tool o CSFs for medium- and high-level ICT users, including o Best Practice Profiles o Action Statements The material contained in this Guide has been generated following a number of principles: o For a given situation there is not a single ‘right answer’, but a number of solutions that have to be evaluated using a range of relevant factors. o Since there are as many solutions as there are ‘solvers’, factors for evaluation will ‘emerge’ from collective wisdom.
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The host specificity of the five published sewage-associated Bacteroides markers (i.e., HF183, BacHum, HuBac, BacH and Human-Bac) was evaluated in Southeast Queensland, Australia by testing fecal DNA samples (n = 186) from 11 animal species including human fecal samples collected via influent to a sewage treatment plant (STP). All human fecal samples (n = 50) were positive for all five markers indicating 100% sensitivity of these markers. The overall specificity of the HF183 markers to differentiate between humans and animals was 99%. The specificities of the BacHum and BacH markers were > 94%, suggesting that these markers are suitable for sewage pollution in environmental waters in Australia. The BacHum (i.e., 63% specificity) and Human-Bac (i.e., 79% specificity) markers performed poorly in distinguishing between the sources of human and animal fecal samples. It is recommended that the specificity of the sewage-associated markers must be rigorously tested prior to its application to identify the sources of fecal pollution in environmental waters.
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Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.
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Investigated the psychometric properties of the original and alternate sets of the Trail Making Test (TMT) and the Controlled Oral Word Association Test (COWAT; A. L. Benton and D. Hamsher, 1978) in 50 orthopedic and 15 closed head injured (1 yr after trauma) patients (aged 15–59 yrs). Although the alternate forms of both measures proved to be stable and consistent with each other in both groups, only the parallel sets of TMT reliably discriminated the clinical group from controls. Practice effects in the head injured were significant only for Trail B of TMT. Factor analysis of the control group's results identified Verbal Knowledge as a major contributor to performance on COWAT, whereas TMT was more dependent on Rapid Visual Search and Visuomotor Sequencing.
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Purpose: To investigate whether wearing different presbyopic vision corrections alters the pattern of eye and head movements when viewing and responding to driving-related traffic scenes. Methods: Participants included 20 presbyopes (mean age: 56.1 ± 5.7 years) who had no experience of wearing presbyopic vision corrections, apart from single vision (SV) reading spectacles. Each participant wore five different vision corrections: distance SV lenses, progressive addition spectacle lenses (PAL), bifocal spectacle lenses (BIF), monovision (MV) and multifocal contact lenses (MTF CL). For each visual condition, participants were required to view videotape recordings of traffic scenes, track a reference vehicle, and identify a series of peripherally presented targets. Digital numerical display panels were also included as near visual stimuli (simulating the visual displays of a vehicle speedometer and radio). Eye and head movements were measured, and the accuracy of target recognition was also recorded. Results: The path length of eye movements while viewing and responding to driving-related traffic scenes was significantly longer when wearing BIF and PAL than MV and MTF CL (both p ≤ 0.013). The path length of head movements was greater with SV, BIF, and PAL than MV and MTF CL (all p < 0.001). Target recognition and brake response times were not significantly affected by vision correction, whereas target recognition was less accurate when the near stimulus was located at eccentricities inferiorly and to the left, rather than directly below the primary position of gaze (p = 0.008), regardless of vision correction. Conclusions: Different presbyopic vision corrections alter eye and head movement patterns. The longer path length of eye and head movements and greater number of saccades associated with the spectacle presbyopic corrections may affect some aspects of driving performance.
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Place branding has become a major focus of operations for destination marketing organizations (DMOs) striving for differentiation in cluttered markets. The topic of destination branding has only received attention in the tourism literature since the late 1990s, and there has been relatively little research reported in relations to analyzing destination brand effectiveness over time. This article reports an attempt to oprationalize the concept of consumer-based brand equity (CBBE) for an emerging destination over two points in time. The purpose of the project was to track the effectiveness of the brand in 2007 against benchmarks that were established in a 2003 student at the commencement of a new destination brand campaign. The key finding was there was no change in perceived performance for the destination across the brand's performance indicators and CBBE dimensions. Because of the common challenges faced by DMOs worldwide, it is suggested the CBBE hierarchy provides destination marketers with a practical tool for evaluation brand performance over time.
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In the emerging literature related to destination branding, little has been reported about performance metrics. The focus of most research reported to date has been concerned with the development of destination brand identities and the implementation of campaigns (see for example, Crockett & Wood 1999, Hall 1999, May 2001, Morgan et al 2002). One area requiring increased attention is that of tracking the performance of destination brands over time. This is an important gap in the tourism literature, given: i) the increasing level of investment by destination marketing organisations (DMO) in branding since the 1990s, ii) the complex political nature of DMO brand decision-making and increasing accountability to stakeholders (see Pike, 2005), and iii) the long-term nature of repositioning a destination’s image in the market place (see Gartner & Hunt, 1987). Indeed, a number of researchers in various parts of the world have pointed to a lack of market research monitoring destination marketing objectives, such as in Australia (see Prosser et. al 2000, Carson, Beattie and Gove 2003), North America (Sheehan & Ritchie 1997, Masberg 1999), and Europe (Dolnicar & Schoesser 2003)...
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Acoustically, vehicles are extremely noisy environments and as a consequence audio-only in-car voice recognition systems perform very poorly. Seeing that the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem. However, implementing such an approach requires a system being able to accurately locate and track the driver’s face and facial features in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using this system, we present our results which show that using the Viola-Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose.
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We aimed to investigate the naturally occurring horizontal plane movements of a head stabilized in a standard ophthalmic headrest and to analyze their magnitude, velocity, spectral characteristics, and correlation to the cardio pulmonary system. Two custom-made air-coupled highly accurate (±2 μm)ultrasound transducers were used to measure the displacements of the head in different horizontal directions with a sampling frequency of 100 Hz. Synchronously to the head movements, an electrocardiogram (ECG) signal was recorded. Three healthy subjects participated in the study. Frequency analysis of the recorded head movements and their velocities was carried out, and functions of coherence between the two displacements and the ECG signal were calculated. Frequency of respiration and the heartbeat were clearly visible in all recorded head movements. The amplitude of head displacements was typically in the range of ±100 μm. The first harmonic of the heartbeat (in the range of 2–3 Hz), rather than its principal frequency, was found to be the dominant frequency of both head movements and their velocities. Coherence analysis showed high interdependence between the considered signals for frequencies of up to 20 Hz. These findings may contribute to the design of better ophthalmic headrests and should help other studies in the decision making of whether to use a heavy headrest or a bite bar.
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This paper presents an analysis of phasor measurement method for tracking the fundamental power frequency to show if it has the performance necessary to cope with the requirements of power system protection and control. In this regard, several computer simulations presenting the conditions of a typical power system signal especially those highly distorted by harmonics, noise and offset, are provided to evaluate the response of the Phasor Measurement (PM) technique. A new method, which can shorten the delay of estimation, has also been proposed for the PM method to work for signals free of even-order harmonics.
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Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.
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This paper presents an object tracking system that utilises a hybrid multi-layer motion segmentation and optical flow algorithm. While many tracking systems seek to combine multiple modalities such as motion and depth or multiple inputs within a fusion system to improve tracking robustness, current systems have avoided the combination of motion and optical flow. This combination allows the use of multiple modes within the object detection stage. Consequently, different categories of objects, within motion or stationary, can be effectively detected utilising either optical flow, static foreground or active foreground information. The proposed system is evaluated using the ETISEO database and evaluation metrics and compared to a baseline system utilising a single mode foreground segmentation technique. Results demonstrate a significant improvement in tracking results can be made through the incorporation of the additional motion information.