Modeling Garment Seam from a Single Image

We propose an automatic garment seam modeling framework to create a garment model with the seam structure from a single image. In order to achieve this, a marked seam image database and parametric seam models have been set up. Given a real seam image, we first identify the type of the seam image based on our marked semn image database and the seam parameters are parsed automatically by our sewing thread estimation method. Second the seam initial model is generated through the pre-defined parametric seam models. A garment model with the seam structure is finally obtained based on the seam position infrmation which users have marked on the garment. Moreover. we verify the effectiveness of our method with numerous experiments.

Calcium channel blockers improve prognosis of patients with coronavirus disease 2019 and hypertension

Background:Hypertension is considered an important risk factor for the coronavirus disease 2019(COVID-19).The commonly anti-hypertensive drugs are the renin-angiotensin-aldosterone system(RAAS)inhibitors,calcium channel blockers(CCBs),and beta-blockers.The association between commonly used anti-hypertensive medications and the clinical outcome of COVID-19 patients with hypertension has not been well studied.Methods:We conducted a retrospective cohort study that included all patients admitted with COVID-19 to Huo Shen Shan Hospital and Guanggu District of the Maternal and Child Health Hospital of Hubei Province,Wuhan,China.Clinical and laboratory characteristics were extracted from electronic medical records.Hypertension and anti-hypertensive treatment were confirmed by medical history and clinical records.The primary clinical endpoint was all-cause mortality.Secondary endpoints included the rates of patients in common wards transferred to the intensive care unit and hospital stay duration.Logistic regression was used to explore the risk factors associated with mortality and prognosis.Propensity score matching was used to balance the confounders between different anti-hypertensive treatments.Kaplan-Meier curves were used to compare the cumulative recovery rate.Log-rank tests were performed to test for differences in Kaplan-Meier curves between different groups.Results:Among 4569 hospitalized patients with COVID-19,31.7%(1449/4569)had a history of hypertension.There were significant differences in mortality rates between hypertensive patients with CCBs(7/359)and those without(21/359)(1.95%vs.5.85%,risk ratio[RR]:0.32,95% confidence interval[CI]:0.13–0.76,χ^(2)=7.61,P=0.0058).After matching for confounders,the mortality rates were similar between the RAAS inhibitor(4/236)and non-RAAS inhibitor(9/236)cohorts(1.69% vs.3.81%,RR:0.43,95% CI:0.13–1.43,χ^(2)=1.98,P=0.1596).Hypertensive patients with beta-blockers(13/340)showed no statistical difference in mortality compared with those without(11/340)(3.82% vs.3.24%,RR:1.19,95% CI:0.53–2.69,χ^(2)=0.17,P=0.6777).Conclusions:In our study,we did not find any positive or negative effects of RAAS inhibitors or beta-blockers in COVID-19 patients with hypertension,while CCBs could improve prognosis.

Modeling yarn-level geometry from a single micro-image

Different types of cloth show distinctive appearances owing to their unique yarn-level geometrical details.Despite its importance in applications such as cloth rendering and simulation,capturing yarn-level geometry is nontrivial and requires special hardware,e.g.,computed tomography scanners,for conventional methods.In this paper,we propose a novel method that can produce the yarn-level geometry of real cloth using a single micro-image,captured by a consumer digital camera with a macro lens.Given a single input image,our method estimates the large-scale yarn geometry by image shading,and the fine-scale fiber details can be recovered via the proposed fiber tracing and generation algorithms.Experimental results indicate that our method can capture the detailed yarn-level geometry of a wide range of cloth and reproduce plausible cloth appearances.