Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly,meaning that skeleton s...Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly,meaning that skeleton structure information is not utilized and multi-view pose information is not completely fused.Moreover,existing graph convolutional operations do not consider the specificity of different joints and different views of pose information when processing skeleton graphs,making the correlation weights between nodes in the graph and their neighborhood nodes shared.Existing Graph Convolutional Networks(GCNs)cannot extract global and deeplevel skeleton structure information and view correlations efficiently.To solve these problems,pre-estimated multiview 2D poses are designed as a multi-view skeleton graph to fuse skeleton priors and view correlations explicitly to process occlusion problem,with the skeleton-edge and symmetry-edge representing the structure correlations between adjacent joints in each viewof skeleton graph and the view-edge representing the view correlations between the same joints in different views.To make graph convolution operation mine elaborate and sufficient skeleton structure information and view correlations,different correlation weights are assigned to different categories of neighborhood nodes and further assigned to each node in the graph.Based on the graph convolution operation proposed above,a Residual Graph Convolution(RGC)module is designed as the basic module to be combined with the simplified Hourglass architecture to construct the Hourglass-GCN as our 3D pose estimation network.Hourglass-GCNwith a symmetrical and concise architecture processes three scales ofmulti-viewskeleton graphs to extract local-to-global scale and shallow-to-deep level skeleton features efficiently.Experimental results on common large 3D pose dataset Human3.6M and MPI-INF-3DHP show that Hourglass-GCN outperforms some excellent methods in 3D pose estimation accuracy.展开更多
The estimation of shear strength of rock mass discontinuity is always a focal, but difficult, problem in the field of geotechnical engineering. Considering the disadvantages and limitation of exist- ing estimation met...The estimation of shear strength of rock mass discontinuity is always a focal, but difficult, problem in the field of geotechnical engineering. Considering the disadvantages and limitation of exist- ing estimation methods, a new approach based on the shadow area percentage （SAP） that can be used to quantify surface roughness is proposed in this article. Firstly, by the help of laser scanning technique, the three-dimensional model of the surface of rock discontinuity was established. Secondly, a light source was simulated, and there would be some shadows produced on the model surface. Thirdly, to obtain the value of SAP of each specimen, the shadow detection technique was introduced for use. Fourthly, compared with the result from direct shear testing and based on statistics, an empirical for- mula was found among SAP, normal stress, and shear strength. Data of Yujian （~ River were used as an example, and the following conclusions have been made. （1） In the case of equal normal stress, the peak shear stress is positively proportional to the SAP. （2） The formula for estimating was derived, and the predictions of peak-shear strength made with this equation well agreed with the experimental re- suits obtained in laboratory tests.展开更多
Advancements in deep learning have considerably enhanced techniques for Rapid Entire Body Assess-ment(REBA)pose estimation by leveraging progress in three-dimensional human modeling.This survey provides an extensive o...Advancements in deep learning have considerably enhanced techniques for Rapid Entire Body Assess-ment(REBA)pose estimation by leveraging progress in three-dimensional human modeling.This survey provides an extensive overview of recent advancements,particularly emphasizing monocular image-based methodologies and their incorporation into ergonomic risk assessment frameworks.By reviewing literature from 2016 to 2024,this study offers a current and comprehensive analysis of techniques,existing challenges,and emerging trends in three-dimensional human pose estimation.In contrast to traditional reviews organized by learning paradigms,this survey examines how three-dimensional pose estimation is effectively utilized within musculoskeletal disorder(MSD)assessments,focusing on essential advancements,comparative analyses,and ergonomic implications.We extend existing image-based clas-sification schemes by examining state-of-the-art two-dimensional models that enhance monocular three-dimensional prediction accuracy and analyze skeleton representations by evaluating joint connectivity and spatial configuration,offering insights into how structural variability influences model robustness.A core contribution of this work is the identification of a critical research gap:the limited exploration of estimating REBA scores directly from single RGB images using monocular three-dimensional pose estimation.Most existing studies depend on depth sensors or sequential inputs,limiting applicability in real-time and resource-constrained environments.Our review emphasizes this gap and proposes future research directions to develop accurate,lightweight,and generalizable models suitable for practical deployment.This survey is a valuable resource for researchers and practitioners in computer vision,ergonomics,and related disciplines,offering a structured understanding of current methodologies and guidance for future innovation in three-dimensional human pose estimation for REBA-based ergonomic risk assessment.展开更多
This paper presents alternating direction finite volume element methods for three-dimensional parabolic partial differential equations and gives four computational schemes, one is analogous to Douglas finite differenc...This paper presents alternating direction finite volume element methods for three-dimensional parabolic partial differential equations and gives four computational schemes, one is analogous to Douglas finite difference scheme with second-order splitting error, the other two schemes have third-order splitting error, and the last one is an extended LOD scheme. The L2 norm and H1 semi-norm error estimates are obtained for the first scheme and second one, respectively. Finally, two numerical examples are provided to illustrate the efficiency and accuracy of the methods.展开更多
In this paper, we propose a new algorithm for temporally consistent depth map estimation to generate three-dimensional video. The proposed algorithm adaptively computes the matching cost using a temporal weighting fun...In this paper, we propose a new algorithm for temporally consistent depth map estimation to generate three-dimensional video. The proposed algorithm adaptively computes the matching cost using a temporal weighting function, which is obtained by block-based moving object detection and motion estimation with variable block sizes. Experimental results show that the proposed algorithm improves the temporal consistency of the depth video and reduces by about 38% both the flickering artefact in the synthesized view and the number of coding bits for depth video coding.展开更多
Petroleum science has made remarkable progress in organic geochcmistry and in the research into the theories of petroleum origin, its transport and accumulation. In estimating the oil-gas resources of a basin, the kno...Petroleum science has made remarkable progress in organic geochcmistry and in the research into the theories of petroleum origin, its transport and accumulation. In estimating the oil-gas resources of a basin, the knowledge of its evolutionary history and especially the numerical computation of fluid flow and the history of its changes under heat is vital. The mathematical model can be described as a coupled system of nonlinear partial differentical equations with initial-boundary value problems. This thesis, from actual conditions such as the effect of fluid compressibility and the three-dimensional characteristic of large-scale science-engineering computation, we put forward a kind of characteristic finite element alternating-direction schemes and obtain optimal order estimates in L^2 norm for the error in the approximate assumption.展开更多
The software for oil-gas transport and accumulation is to describe the history of oil-gas transport and accumulation in basin evolution. It is of great value in rational evaluation of prospecting and exploiting oil-ga...The software for oil-gas transport and accumulation is to describe the history of oil-gas transport and accumulation in basin evolution. It is of great value in rational evaluation of prospecting and exploiting oil-gas resources. The mathematical model can be discribed as a coupled system of nonlinear partial differential equations with moving boundary value problem. For a generic case of the three-demensional bounded region, bi this thesis, the effects of gravitation、buoyancy and capillary pressure are considered, we put forward a kind of characteristic finite difference schemes and make use thick and thin grids to form a complete set, and of calculus of vaviations, the change of variable, the theory of prior estimates and techniques, Optimal order estimates in l^2 norm are derived for the error in approximate assumption, Thus we have completely solved the well-known theoretical problem proposed by J. Douglas, Jr.展开更多
In this Letter, we propose a novel three-dimeusional （3D） color microscopy for microorganisms under photon- starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori info...In this Letter, we propose a novel three-dimeusional （3D） color microscopy for microorganisms under photon- starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori infor- mation. In photon counting integral imaging, 3D images can be visualized using maximum likelihood estimation （MLE）. However, since MLE does not consider a priori information of objects, the visual quality of 3D images may not be accurate. In addition, the only grayscale image can be reconstructed. Therefore, to enhance the visual quality of 3D images, we propose photon counting microscopy using maximum a posteriori with adaptive priori information. In addition, we consider a wavelength of each basic color channel to reconstruct 3D color images. To verify our proposed method, we carry out optical experiments.展开更多
Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information.The physical effort represents the work hardness used to optimize wearable ...Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information.The physical effort represents the work hardness used to optimize wearable robotic systems.Thus,personalization and rapid optimization of the effort are critical.Although respirometry is the gold standard for estimating metabolic costs,this method requires a heavy,bulky,and rigid system,limiting the system’s field deployability.Here,this paper reports a soft,flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton,used to estimate metabolic costs and physical effort,demonstrating the potential for real-time wearable robot adjustments based on biofeedback.Data from a set of activities,including walking,running,and squatting with the biopatch and exoskeleton,determines the relationship between metabolic costs and heart rate variability root mean square of successive differences(HRV-RMSSD)(R=−0.758).Collectively,the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.展开更多
The accurate identification of various postures in the daily life of piglets that are directly reflected by their skeleton morphology is necessary to study the behavioral characteristics of pigs.Accordingly,this study...The accurate identification of various postures in the daily life of piglets that are directly reflected by their skeleton morphology is necessary to study the behavioral characteristics of pigs.Accordingly,this study proposed a novel approach for the skeleton extraction and pose estimation of piglets.First,an improved Zhang-Suen(ZS)thinning algorithm based on morphology was used to establish the chain code mechanism of the burr and the redundant information deletion templates to achieve a single-pixel width extraction of pig skeletons.Then,body nodes were extracted on the basis of the improved DeepLabCut(DLC)algorithm,and a part affinity field(PAF)was added to realize the connection of body nodes,and consequently,construct a database of pig behavior and postures.Finally,a support vector machine was used for pose matching to recognize the main behavior of piglets.In this study,14000 images of piglets with different types of behavior were used in posture recognition experiments.Results showed that the improved algorithm based on ZS-DLC-PAF achieved the best thinning rate compared with those of distance transformation,medial axis transformation,morphology refinement,and the traditional ZS algorithm.The node tracking accuracy reached 85.08%,and the pressure test could accurately detect up to 35 nodes of 5 pigs.The average accuracy of posture matching was 89.60%.This study not only realized the single-pixel extraction of piglets’skeletons but also the connection among the different behavior body nodes of individual sows and multiple piglets.Furthermore,this study established a database of pig posture behavior,which provides a reference for studying animal behavior identification and classification and anomaly detection.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 61973065,U20A20197,61973063.
文摘Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly,meaning that skeleton structure information is not utilized and multi-view pose information is not completely fused.Moreover,existing graph convolutional operations do not consider the specificity of different joints and different views of pose information when processing skeleton graphs,making the correlation weights between nodes in the graph and their neighborhood nodes shared.Existing Graph Convolutional Networks(GCNs)cannot extract global and deeplevel skeleton structure information and view correlations efficiently.To solve these problems,pre-estimated multiview 2D poses are designed as a multi-view skeleton graph to fuse skeleton priors and view correlations explicitly to process occlusion problem,with the skeleton-edge and symmetry-edge representing the structure correlations between adjacent joints in each viewof skeleton graph and the view-edge representing the view correlations between the same joints in different views.To make graph convolution operation mine elaborate and sufficient skeleton structure information and view correlations,different correlation weights are assigned to different categories of neighborhood nodes and further assigned to each node in the graph.Based on the graph convolution operation proposed above,a Residual Graph Convolution(RGC)module is designed as the basic module to be combined with the simplified Hourglass architecture to construct the Hourglass-GCN as our 3D pose estimation network.Hourglass-GCNwith a symmetrical and concise architecture processes three scales ofmulti-viewskeleton graphs to extract local-to-global scale and shallow-to-deep level skeleton features efficiently.Experimental results on common large 3D pose dataset Human3.6M and MPI-INF-3DHP show that Hourglass-GCN outperforms some excellent methods in 3D pose estimation accuracy.
基金supported by the China Geological Survey (No.1212011014030)the Major State Basic Research Development Program of China (973 Program) (No.2011CB710600)
文摘The estimation of shear strength of rock mass discontinuity is always a focal, but difficult, problem in the field of geotechnical engineering. Considering the disadvantages and limitation of exist- ing estimation methods, a new approach based on the shadow area percentage （SAP） that can be used to quantify surface roughness is proposed in this article. Firstly, by the help of laser scanning technique, the three-dimensional model of the surface of rock discontinuity was established. Secondly, a light source was simulated, and there would be some shadows produced on the model surface. Thirdly, to obtain the value of SAP of each specimen, the shadow detection technique was introduced for use. Fourthly, compared with the result from direct shear testing and based on statistics, an empirical for- mula was found among SAP, normal stress, and shear strength. Data of Yujian （~ River were used as an example, and the following conclusions have been made. （1） In the case of equal normal stress, the peak shear stress is positively proportional to the SAP. （2） The formula for estimating was derived, and the predictions of peak-shear strength made with this equation well agreed with the experimental re- suits obtained in laboratory tests.
文摘Advancements in deep learning have considerably enhanced techniques for Rapid Entire Body Assess-ment(REBA)pose estimation by leveraging progress in three-dimensional human modeling.This survey provides an extensive overview of recent advancements,particularly emphasizing monocular image-based methodologies and their incorporation into ergonomic risk assessment frameworks.By reviewing literature from 2016 to 2024,this study offers a current and comprehensive analysis of techniques,existing challenges,and emerging trends in three-dimensional human pose estimation.In contrast to traditional reviews organized by learning paradigms,this survey examines how three-dimensional pose estimation is effectively utilized within musculoskeletal disorder(MSD)assessments,focusing on essential advancements,comparative analyses,and ergonomic implications.We extend existing image-based clas-sification schemes by examining state-of-the-art two-dimensional models that enhance monocular three-dimensional prediction accuracy and analyze skeleton representations by evaluating joint connectivity and spatial configuration,offering insights into how structural variability influences model robustness.A core contribution of this work is the identification of a critical research gap:the limited exploration of estimating REBA scores directly from single RGB images using monocular three-dimensional pose estimation.Most existing studies depend on depth sensors or sequential inputs,limiting applicability in real-time and resource-constrained environments.Our review emphasizes this gap and proposes future research directions to develop accurate,lightweight,and generalizable models suitable for practical deployment.This survey is a valuable resource for researchers and practitioners in computer vision,ergonomics,and related disciplines,offering a structured understanding of current methodologies and guidance for future innovation in three-dimensional human pose estimation for REBA-based ergonomic risk assessment.
文摘This paper presents alternating direction finite volume element methods for three-dimensional parabolic partial differential equations and gives four computational schemes, one is analogous to Douglas finite difference scheme with second-order splitting error, the other two schemes have third-order splitting error, and the last one is an extended LOD scheme. The L2 norm and H1 semi-norm error estimates are obtained for the first scheme and second one, respectively. Finally, two numerical examples are provided to illustrate the efficiency and accuracy of the methods.
基金supported by the National Research Foundation of Korea Grant funded by the Korea Ministry of Science and Technology under Grant No. 2012-0009228
文摘In this paper, we propose a new algorithm for temporally consistent depth map estimation to generate three-dimensional video. The proposed algorithm adaptively computes the matching cost using a temporal weighting function, which is obtained by block-based moving object detection and motion estimation with variable block sizes. Experimental results show that the proposed algorithm improves the temporal consistency of the depth video and reduces by about 38% both the flickering artefact in the synthesized view and the number of coding bits for depth video coding.
基金Project supported by the National Science Foundation,the National Scaling Programthe Doctoral Foundation of the National Education Commission
文摘Petroleum science has made remarkable progress in organic geochcmistry and in the research into the theories of petroleum origin, its transport and accumulation. In estimating the oil-gas resources of a basin, the knowledge of its evolutionary history and especially the numerical computation of fluid flow and the history of its changes under heat is vital. The mathematical model can be described as a coupled system of nonlinear partial differentical equations with initial-boundary value problems. This thesis, from actual conditions such as the effect of fluid compressibility and the three-dimensional characteristic of large-scale science-engineering computation, we put forward a kind of characteristic finite element alternating-direction schemes and obtain optimal order estimates in L^2 norm for the error in the approximate assumption.
基金Project supported by the National Scaling Program,the National Eighth-Five-Year Tackling Key Problem Programthe Doctoral Program Foundation of the National Education Commission
文摘The software for oil-gas transport and accumulation is to describe the history of oil-gas transport and accumulation in basin evolution. It is of great value in rational evaluation of prospecting and exploiting oil-gas resources. The mathematical model can be discribed as a coupled system of nonlinear partial differential equations with moving boundary value problem. For a generic case of the three-demensional bounded region, bi this thesis, the effects of gravitation、buoyancy and capillary pressure are considered, we put forward a kind of characteristic finite difference schemes and make use thick and thin grids to form a complete set, and of calculus of vaviations, the change of variable, the theory of prior estimates and techniques, Optimal order estimates in l^2 norm are derived for the error in approximate assumption, Thus we have completely solved the well-known theoretical problem proposed by J. Douglas, Jr.
基金supported in part by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,Information and Communications TechnologiesFuture Planning(No.2011-0030079)Basic Science Research Program through the NRF funded by the Ministry of Education(NRF-2013R1A1A2057549)
文摘In this Letter, we propose a novel three-dimeusional （3D） color microscopy for microorganisms under photon- starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori infor- mation. In photon counting integral imaging, 3D images can be visualized using maximum likelihood estimation （MLE）. However, since MLE does not consider a priori information of objects, the visual quality of 3D images may not be accurate. In addition, the only grayscale image can be reconstructed. Therefore, to enhance the visual quality of 3D images, we propose photon counting microscopy using maximum a posteriori with adaptive priori information. In addition, we consider a wavelength of each basic color channel to reconstruct 3D color images. To verify our proposed method, we carry out optical experiments.
基金the National Science Foundation/the Centers for Disease Control and Prevention(grant NRI‐2024742)supported by the IEN Center Grant from the Georgia Tech Institute for Electronics and Nanotechnologysupported by the National Science Foundation(grant ECCS-2025462).
文摘Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information.The physical effort represents the work hardness used to optimize wearable robotic systems.Thus,personalization and rapid optimization of the effort are critical.Although respirometry is the gold standard for estimating metabolic costs,this method requires a heavy,bulky,and rigid system,limiting the system’s field deployability.Here,this paper reports a soft,flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton,used to estimate metabolic costs and physical effort,demonstrating the potential for real-time wearable robot adjustments based on biofeedback.Data from a set of activities,including walking,running,and squatting with the biopatch and exoskeleton,determines the relationship between metabolic costs and heart rate variability root mean square of successive differences(HRV-RMSSD)(R=−0.758).Collectively,the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.
基金This work was financially supported by the National Major Science and Technology Project(Innovation 2030)of China(Grant No.2021ZD0113701).
文摘The accurate identification of various postures in the daily life of piglets that are directly reflected by their skeleton morphology is necessary to study the behavioral characteristics of pigs.Accordingly,this study proposed a novel approach for the skeleton extraction and pose estimation of piglets.First,an improved Zhang-Suen(ZS)thinning algorithm based on morphology was used to establish the chain code mechanism of the burr and the redundant information deletion templates to achieve a single-pixel width extraction of pig skeletons.Then,body nodes were extracted on the basis of the improved DeepLabCut(DLC)algorithm,and a part affinity field(PAF)was added to realize the connection of body nodes,and consequently,construct a database of pig behavior and postures.Finally,a support vector machine was used for pose matching to recognize the main behavior of piglets.In this study,14000 images of piglets with different types of behavior were used in posture recognition experiments.Results showed that the improved algorithm based on ZS-DLC-PAF achieved the best thinning rate compared with those of distance transformation,medial axis transformation,morphology refinement,and the traditional ZS algorithm.The node tracking accuracy reached 85.08%,and the pressure test could accurately detect up to 35 nodes of 5 pigs.The average accuracy of posture matching was 89.60%.This study not only realized the single-pixel extraction of piglets’skeletons but also the connection among the different behavior body nodes of individual sows and multiple piglets.Furthermore,this study established a database of pig posture behavior,which provides a reference for studying animal behavior identification and classification and anomaly detection.
