Remote gaze estimation systems use calibration procedures to estimate subject-specific parameters that are needed for the calculation of the point-of-gaze. In these procedures, subjects are required to fixate on a specific point or points at specific time instances. Advanced remote gaze estimation systems can estimate the optical axis of the eye without any personal calibration procedure, but use a single calibration point to estimate the angle between the optical axis and the visual axis (line-of-sight). This paper presents a novel automatic calibration procedure that does not require active user participation. To estimate the angles between the optical and visual axes of each eye, this procedure minimizes the distance between the intersections of the visual axes of the left and right eyes with the surface of a display while subjects look naturally at the display (e.g., watching a video clip). Simulation results demonstrate that the performance of the algorithm improves as the range of viewing angles increases. For a subject sitting 75 cm in front of an 80 cm x 60 cm display (40" TV) the standard deviation of the error in the estimation of the angles between the optical and visual axes is 0.5 degrees.
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http://dx.doi.org/10.1109/IEMBS.2009.5334183 | DOI Listing |
BMC Pediatr
January 2025
Department of Orthodontics, University Hospital Bonn, Medical Faculty, Welschnonnenstr. 17, 53111, Bonn, Germany.
Background: Children with non-syndromic cleft lip with or without palate (CL ± P) may present alterations in dental development. The purpose of this cross-sectional study was to compare the dental age (DA) between children with and without CL ± P, and whether single nucleotide polymorphisms (SNPs) in genes encoding growth factors are associated with DA variations.
Methods: Children aged between 5 and 14 years with and without CL ± P were recruited to participate in this study.
BMC Geriatr
January 2025
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Background: During the COVID-19 pandemic, nursing home (NH) residents faced the highest risk of severe COVID-19 disease and mortality. Due to their frailty status, comorbidity burden can serve as a useful predictive indicator of vulnerability in this frail population. However, the prognostic value of these cumulative comorbidity scores like the Charlson comorbidity index (CCI) remained unclear in this population.
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January 2025
School of Mathematics and Statistics, Central South University, Changsha, 410083, China.
The coronavirus disease 2019 (COVID-19) interventions in interrupting transmission have paid heavy losses politically and economically. The Chinese government has replaced scaling up testing with monitoring focus groups and randomly supervising sampling, encouraging scientific research on the COVID-19 transmission curve to be confirmed by constructing epidemiological models, which include statistical models, computer simulations, mathematical illustrations of the pathogen and its effects, and several other methodologies. Although predicting and forecasting the propagation of COVID-19 are valuable, they nevertheless present an enormous challenge.
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January 2025
School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New City, Tangshan City, 063210, Hebei Province, China.
This study aims to explore the association between the triglyceride-glucose (TyG) index and the risk of carotid atherosclerosis (CAS) among Chinese steelworkers. This is a cross-sectional study involving a total of 4,203 Chinese steelworkers. The TyG index was calculated using the formula: TyG = Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL) / 2].
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
LMFE, Faculty of Sciences Semlalia, Cadi Ayyad University, 40000, Marrakesh, Morocco.
In the last decades, natural and anthropogenic pressures have caused observable changes in the argan landscape despite its significance in Morocco. Remote sensing data can be used to monitor these changes over time and provide information on vegetation health and land cover changes. This study assesses the performance of supervised methods (support vector machine, maximum likelihood, and minimum distance) and unsupervised classification method (Isodata) for mapping the argan forest in the Smimou area of Essaouira province using remote sensing data from Landsat-5 and Landsat-8 (1985 and 2019).
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