In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In additi...In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.展开更多
We conducted a comprehensive genetic investigation of obesity in a cohort of 93,673 Korean individuals,categorized by body mass index and waist circumference using Korean-specific and international criteria.To explore...We conducted a comprehensive genetic investigation of obesity in a cohort of 93,673 Korean individuals,categorized by body mass index and waist circumference using Korean-specific and international criteria.To explore the genetic architecture of obesity and its related comorbidities,we performed genome-wide association studies and constructed polygenic risk scores(PRSs)using both conventional single-trait and advanced multiple-trait models,including the PRSsum approach.Our analyses identified genome-wide significant loci and demonstrated their higher heritability for general obesity than for abdominal obesity,and for moderate obesity than for severe obesity.East Asian populations showed stronger genetic correlations between abdominal obesity and obesity-related diseases.Both single-trait and multiple-trait PRSs stratified individuals by risk,with low-PRS individuals exhibiting reduced risk for obesity,hypertension,and type 2 diabetes,while high-PRS individuals displayed elevated risk,particularly under the multiple-trait model.Interaction and mediation analyses revealed distinct genetic pathways through which obesity contributes to disease development.Collectively,our findings revealed key loci and shared genetic mechanisms linking obesity and its comorbidities in the Korean population.These insights highlight the value of multiple-trait PRS models and underscore the importance of ancestry-specific genetic research for addressing the obesity epidemic.展开更多
基金supported by the 2024 Research Fund of University of Ulsan.
文摘In recent years,three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly,enabling remote collaboration among users in extended Reality(XR)environments.In addition,methods for deploying multiple cameras for motion capture of users(e.g.,performers)are widely used in computer graphics.As the need to minimize and optimize the number of cameras grows to reduce costs,various technologies and research approaches focused on Optimal Camera Placement(OCP)are continually being proposed.However,as most existing studies assume homogeneous camera setups,there is a growing demand for studies on heterogeneous camera setups.For instance,technical demands keep emerging in scenarios with minimal camera configurations,especially regarding cost factors,the physical placement of cameras given the spatial structure,and image capture strategies for heterogeneous cameras,such as high-resolution RGB cameras and depth cameras.In this study,we propose a pre-visualization and simulation method for the optimal placement of heterogeneous cameras in XR environments,accounting for both the specifications of heterogeneous cameras(e.g.,field of view)and the physical configuration(e.g.,wall configuration)in real-world spaces.The proposed method performs a visibility analysis of cameras by considering each camera’s field-of-view volume,resolution,and unique characteristics,along with physicalspace constraints.This approach enables the optimal position and rotation of each camera to be recommended,along with the minimum number of cameras required.In the results of our study conducted in heterogeneous camera combinations,the proposed method achieved 81.7%~82.7%coverage of the target visual information using only 2~3 cameras.In contrast,single(or homogeneous)-typed cameras were required to use 11 cameras for 81.6%coverage.Accordingly,we found that camera deployment resources can be reduced with the proposed approaches.
基金National Biobank of Korea,the Korea Disease Control and Prevention Agency,Republic of Korea(Grant No.KBN-2020-101)supported by the National Research Foundation(NRF)of Korea funded by the Korean government(MSIT)(Grant No.RS-2024-00346850)+2 种基金the Bio&Medical Technology Development Program of the NRF funded by the Korean government(MSIT)(Grant No.RS-2025-16063949)the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI)funded by the Ministry of Health&Welfare,Republic of Korea(Grant No.RS-2024-00403700)supported by the National Supercomputing Center,Korea Institute of Science&Technology Information(KISTI),with supercomputing resources including technical support(Grant Nos.KSC-2022-CRE-0319 and KSC-2023-CRE-0117).
文摘We conducted a comprehensive genetic investigation of obesity in a cohort of 93,673 Korean individuals,categorized by body mass index and waist circumference using Korean-specific and international criteria.To explore the genetic architecture of obesity and its related comorbidities,we performed genome-wide association studies and constructed polygenic risk scores(PRSs)using both conventional single-trait and advanced multiple-trait models,including the PRSsum approach.Our analyses identified genome-wide significant loci and demonstrated their higher heritability for general obesity than for abdominal obesity,and for moderate obesity than for severe obesity.East Asian populations showed stronger genetic correlations between abdominal obesity and obesity-related diseases.Both single-trait and multiple-trait PRSs stratified individuals by risk,with low-PRS individuals exhibiting reduced risk for obesity,hypertension,and type 2 diabetes,while high-PRS individuals displayed elevated risk,particularly under the multiple-trait model.Interaction and mediation analyses revealed distinct genetic pathways through which obesity contributes to disease development.Collectively,our findings revealed key loci and shared genetic mechanisms linking obesity and its comorbidities in the Korean population.These insights highlight the value of multiple-trait PRS models and underscore the importance of ancestry-specific genetic research for addressing the obesity epidemic.
