An investigation into determining head pose for gaze estimation on unmodified mobile devices

Traditionally, devices which are able to determine a users gaze are large, expensive and often restrictive. We investigate the prospect of using common webcams and mobile devices such as laptops, tablets and phones without modification as an alternative means for obtaining a users gaze. A person’s gaze can be fundamentally determined by the pose of the head as well as the orientation of the eyes. This initial work investigates the first of these factors - an estimate of the 3D head pose (and subsequently the positions of the eye centres) relative to a camera device. Specifically, we seek a low cost algorithm that requires only a one-time calibration for an individual user, that can run in real-time on the aforementioned mobile devices with noisy camera data. We use our head tracker to estimate the 4 eye corners of a user over a 10 second video. We present the results at several different frames per second (fps) to analyse the impact on the tracker with lower quality cameras. We show that our algorithm is efficient enough to run at 75fps on a common laptop, but struggles with tracking loss when the fps is lower than 10fps

Embedded Eye-Gaze Tracking On Mobile Devices

The eyes are one of the most expressive non-verbal tools a person has and they are able to communicate a great deal to the outside world about the intentions of that person. Being able to decipher these communications through robust and non-intrusive gaze tracking techniques is increasingly important as we look toward improving Human-Computer Interaction (HCI). Traditionally, devices which are able to determine a user's gaze are large, expensive and often restrictive. This work investigates the prospect of using common mobile devices such as tablets and phones as an alternative means for obtaining a user's gaze. Mobile devices now often contain high resolution cameras, and their ever increasing computational power allows increasingly complex algorithms to be performed in real time. A mobile solution allows us to turn that device into a dedicated portable gaze-tracking device for use in a wide variety of situations. This work specifically looks at where the challenges lie in transitioning current state-of-the-art gaze methodologies to mobile devices and suggests novel solutions to counteract the specific challenges of the medium. In particular, when the mobile device is held in the hands fast changes in position and orientation of the user can occur. In addition, since these devices lack the technologies typically ubiquitous to gaze estimation such as infra-red lighting, novel alternatives are required that work under common everyday conditions. A person's gaze can be determined through both their head pose as well as the orientation of the eye relative to the head. To meet the challenges outlined a geometric approach is taken where a new model for each is introduced that by design are completely synchronised through a common origin. First, a novel 3D head-pose estimation model called the 2.5D Constrained Local Model (2.5D CLM) is introduced that directly and reliably obtains the head-pose from a monocular camera. Then, a new model for gaze-estimation is introduced -- the Constrained Geometric Binocular Model (CGBM), where the visual ray representing the gaze from each eye is jointly optimised to intersect a known monitor plane in 3D space. The potential for both is that the burden of calibration is placed on the camera and monitor setup, which on mobile devices are fixed and can be determined during factory construction. In turn, the user requires either no calibration or optionally a one-time estimation of the visual offset angle. This work details the new models and specifically investigates their applicability and suitability in terms of their potential to be used on mobile platforms

What were we all looking at? Identifying objects of collective visual attention

The file attached to this record is the authors final peer reviewed version. The publisher's final version can be found by following the DOI link below.We aim to identify the salient objects in an image by applying a model of visual attention. We automate the process by predicting those objects in an image that are most likely to be the focus of someone’s visual attention. Concretely, we first generate fixation maps from the eye tracking data, which express the ground truth of people’s visual attention for each training image. Then, we extract the high-level features based on the bag-of-visual-words image representation as input attributes along with the fixation maps to train a support vector regression model. With this model, we can predict a new query image’s saliency. Our experiments show that the model is capable of providing a good estimate for human visual attention in test images sets with one salient object and multiple salient objects. In this way, we seek to reduce the redundant information within the scene, and thus provide a more accurate depiction of the scene

Remote Sensing Scene Classification Based on Convolutional Neural Networks Pre-Trained Using Attention-Guided Sparse Filters

Open access articleSemantic-level land-use scene classification is a challenging problem, in which deep learning methods, e.g., convolutional neural networks (CNNs), have shown remarkable capacity. However, a lack of sufficient labeled images has proved a hindrance to increasing the land-use scene classification accuracy of CNNs. Aiming at this problem, this paper proposes a CNN pre-training method under the guidance of a human visual attention mechanism. Specifically, a computational visual attention model is used to automatically extract salient regions in unlabeled images. Then, sparse filters are adopted to learn features from these salient regions, with the learnt parameters used to initialize the convolutional layers of the CNN. Finally, the CNN is further fine-tuned on labeled images. Experiments are performed on the UCMerced and AID datasets, which show that when combined with a demonstrative CNN, our method can achieve 2.24% higher accuracy than a plain CNN and can obtain an overall accuracy of 92.43% when combined with AlexNet. The results indicate that the proposed method can effectively improve CNN performance using easy-to-access unlabeled images and thus will enhance the performance of land-use scene classification especially when a large-scale labeled dataset is unavailable

Randomized trial of short-course radiotherapy versus long-course chemoradiation comparing rates of local recurrence in patients with T3 rectal cancer: Trans-Tasman Radiation Oncology Group Trial 01.04

Glioblastoma is associated with a poor prognosis in the elderly. Survival has been shown to increase among patients 70 years of age or younger when temozolomide chemotherapy is added to standard radiotherapy (60 Gy over a period of 6 weeks). In elderly patients, more convenient shorter courses of radiotherapy are commonly used, but the benefit of adding temozolomide to a shorter course of radiotherapy is unknown

Oral health and elite sport performance

While the research base is limited, studies have consistently reported poor oral health in elite athletes since the first report from the 1968 Olympic Games. The finding is consistent both across selected samples attending dental clinics at major competitions and more representative sampling of teams and has led to calls from the International Olympic Committee for more accurate data on oral health. Poor oral health is an important issue directly as it can cause pain, negative effects on appearance and psychosocial effects on confidence and quality of life and may have long-term consequences for treatment burden. Self-reported evidence also suggests an impact on training and performance of athletes. There are many potential challenges to the oral health of athletes including nutritional, oral dehydration, exercise-induced immune suppression, lack of awareness, negative health behaviours and lack of prioritisation. However, in theory, oral diseases are preventable by simple interventions with good evidence of efficacy. The consensus statement aims to raise awareness of the issues of oral health in elite sport and recommends strategies for prevention and health promotion in addition to future research strategies

Global causes of blindness and distance vision impairment 1990–2020: a systematic review and meta-analysis

Background: Contemporary data on causes of vision impairment and blindness form an important basis for recommendations in public health policies. Refreshment of the Global Vision Database with recently published data sources permitted modeling of cause of vision loss data from 1990 to 2015, further disaggregation by cause, and forecasts to 2020. Methods: Published and unpublished population-based data on the causes of vision impairment and blindness from 1980 to 2015 were systematically analysed. A series of regression models were fit to estimate the proportion of moderate and severe vision impairment (MSVI; defined as presenting visual acuity <6/18 but ≥3/60 in the better eye) and blindness (presenting visual acuity <3/60 in the better eye) by cause by age, region, and year. Findings: Among the projected global population with MSVI (216.6 million; 80% uncertainty intervals [UI] 98.5-359.1), in 2015 the leading causes thereof are uncorrected refractive error (116.3 million; UI 49.4-202.1), cataract (52.6 million; UI 18.2-109.6), age-related macular degeneration (AMD; 8.4 million; UI 0.9-29.5), glaucoma (4.0 million; UI 0.6-13.3) and diabetic retinopathy (2.6 million; UI 0.2-9.9). In 2015, the leading global causes of blindness were cataract (12.6 million; UI 3.4-28.7) followed by uncorrected refractive error (7.4 million; UI 2.4-14.8) and glaucoma (2.9 million; UI 0.4-9.9), while by 2020, these numbers affected are anticipated to rise to 13.4 million, 8.0 million and 3.2 million, respectively. Cataract and uncorrected refractive error combined contributed to 55% of blindness and 77% of MSVI in adults aged 50 years and older in 2015. World regions varied markedly in the causes of blindness, with a relatively low prevalence of cataract and a relatively high prevalence of AMD as causes for vision loss in the High-income subregions. Blindness due to cataract and diabetic retinopathy was more common among women, while blindness due to glaucoma and corneal opacity was more common among men, with no gender difference related to AMD. Conclusions: The numbers of people affected by the common causes of vision loss have increased substantially as the population increases and ages. Preventable vision loss due to cataract and refractive error (reversible with surgery and spectacle correction respectively), continue to cause the majority of blindness and MSVI in adults aged 50+ years. A massive scale up of eye care provision to cope with the increasing numbers is needed if one is to address avoidable vision loss

Effect of a Perioperative, Cardiac Output-Guided Hemodynamic Therapy Algorithm on Outcomes Following Major Gastrointestinal Surgery A Randomized Clinical Trial and Systematic Review

Importance: small trials suggest that postoperative outcomes may be improved by the use of cardiac output monitoring to guide administration of intravenous fluid and inotropic drugs as part of a hemodynamic therapy algorithm.Objective: to evaluate the clinical effectiveness of a perioperative, cardiac output–guided hemodynamic therapy algorithm.Design, setting, and participants: OPTIMISE was a pragmatic, multicenter, randomized, observer-blinded trial of 734 high-risk patients aged 50 years or older undergoing major gastrointestinal surgery at 17 acute care hospitals in the United Kingdom. An updated systematic review and meta-analysis were also conducted including randomized trials published from 1966 to February 2014.Interventions: patients were randomly assigned to a cardiac output–guided hemodynamic therapy algorithm for intravenous fluid and inotrope (dopexamine) infusion during and 6 hours following surgery (n=368) or to usual care (n=366).Main outcomes and measures: the primary outcome was a composite of predefined 30-day moderate or major complications and mortality. Secondary outcomes were morbidity on day 7; infection, critical care–free days, and all-cause mortality at 30 days; all-cause mortality at 180 days; and length of hospital stay.Results: baseline patient characteristics, clinical care, and volumes of intravenous fluid were similar between groups. Care was nonadherent to the allocated treatment for less than 10% of patients in each group. The primary outcome occurred in 36.6% of intervention and 43.4% of usual care participants (relative risk [RR], 0.84 [95% CI, 0.71-1.01]; absolute risk reduction, 6.8% [95% CI, ?0.3% to 13.9%]; P?=?.07). There was no significant difference between groups for any secondary outcomes. Five intervention patients (1.4%) experienced cardiovascular serious adverse events within 24 hours compared with none in the usual care group. Findings of the meta-analysis of 38 trials, including data from this study, suggest that the intervention is associated with fewer complications (intervention, 488/1548 [31.5%] vs control, 614/1476 [41.6%]; RR, 0.77 [95% CI, 0.71-0.83]) and a nonsignificant reduction in hospital, 28-day, or 30-day mortality (intervention, 159/3215 deaths [4.9%] vs control, 206/3160 deaths [6.5%]; RR, 0.82 [95% CI, 0.67-1.01]) and mortality at longest follow-up (intervention, 267/3215 deaths [8.3%] vs control, 327/3160 deaths [10.3%]; RR, 0.86 [95% CI, 0.74-1.00]).Conclusions and relevance: in a randomized trial of high-risk patients undergoing major gastrointestinal surgery, use of a cardiac output–guided hemodynamic therapy algorithm compared with usual care did not reduce a composite outcome of complications and 30-day mortality. However, inclusion of these data in an updated meta-analysis indicates that the intervention was associated with a reduction in complication rate

Magnitude, temporal trends, and projections of the global prevalence of blindness and distance and near vision impairment: a systematic review and meta-analysis

Background: Global and regional prevalence estimates for blindness and vision impairment are important for the development of public health policies. We aimed to provide global estimates, trends, and projections of global blindness and vision impairment. Methods: We did a systematic review and meta-analysis of population-based datasets relevant to global vision impairment and blindness that were published between 1980 and 2015. We fitted hierarchical models to estimate the prevalence (by age, country, and sex), in 2015, of mild visual impairment (presenting visual acuity worse than 6/12 to 6/18 inclusive), moderate to severe visual impairment (presenting visual acuity worse than 6/18 to 3/60 inclusive), blindness (presenting visual acuity worse than 3/60), and functional presbyopia (defined as presenting near vision worse than N6 or N8 at 40 cm when best-corrected distance visual acuity was better than 6/12). Findings: Globally, of the 7·33 billion people alive in 2015, an estimated 36·0 million (80% uncertainty interval [UI] 12·9–65·4) were blind (crude prevalence 0·48%; 80% UI 0·17–0·87; 56% female), 216·6 million (80% UI 98·5–359·1) people had moderate to severe visual impairment (2·95%, 80% UI 1·34–4·89; 55% female), and 188·5 million (80% UI 64·5–350·2) had mild visual impairment (2·57%, 80% UI 0·88–4·77; 54% female). Functional presbyopia affected an estimated 1094·7 million (80% UI 581·1–1686·5) people aged 35 years and older, with 666·7 million (80% UI 364·9–997·6) being aged 50 years or older. The estimated number of blind people increased by 17·6%, from 30·6 million (80% UI 9·9–57·3) in 1990 to 36·0 million (80% UI 12·9–65·4) in 2015. This change was attributable to three factors, namely an increase because of population growth (38·4%), population ageing after accounting for population growth (34·6%), and reduction in age-specific prevalence (–36·7%). The number of people with moderate and severe visual impairment also increased, from 159·9 million (80% UI 68·3–270·0) in 1990 to 216·6 million (80% UI 98·5–359·1) in 2015. Interpretation: There is an ongoing reduction in the age-standardised prevalence of blindness and visual impairment, yet the growth and ageing of the world’s population is causing a substantial increase in number of people affected. These observations, plus a very large contribution from uncorrected presbyopia, highlight the need to scale up vision impairment alleviation efforts at all levels