Swarm robot systems are an important application of autonomous unmanned surface vehicles on water surfaces.For monitoring natural environments and conducting security activities within a certain range using a surface ...Swarm robot systems are an important application of autonomous unmanned surface vehicles on water surfaces.For monitoring natural environments and conducting security activities within a certain range using a surface vehicle,the swarm robot system is more efficient than the operation of a single object as the former can reduce cost and save time.It is necessary to detect adjacent surface obstacles robustly to operate a cluster of unmanned surface vehicles.For this purpose,a LiDAR(light detection and ranging)sensor is used as it can simultaneously obtain 3D information for all directions,relatively robustly and accurately,irrespective of the surrounding environmental conditions.Although the GPS(global-positioning-system)error range exists,obtaining measurements of the surface-vessel position can still ensure stability during platoon maneuvering.In this study,a three-layer convolutional neural network is applied to classify types of surface vehicles.The aim of this approach is to redefine the sparse 3D point cloud data as 2D image data with a connotative meaning and subsequently utilize this transformed data for object classification purposes.Hence,we have proposed a descriptor that converts the 3D point cloud data into 2D image data.To use this descriptor effectively,it is necessary to perform a clustering operation that separates the point clouds for each object.We developed voxel-based clustering for the point cloud clustering.Furthermore,using the descriptor,3D point cloud data can be converted into a 2D feature image,and the converted 2D image is provided as an input value to the network.We intend to verify the validity of the proposed 3D point cloud feature descriptor by using experimental data in the simulator.Furthermore,we explore the feasibility of real-time object classification within this framework.展开更多
To realize the automation of fashion industry measuring,designing and manufacturing, the auto-measurement of 3D size of human body is of great importance. The auto measurement system of 3D human body based on Charge C...To realize the automation of fashion industry measuring,designing and manufacturing, the auto-measurement of 3D size of human body is of great importance. The auto measurement system of 3D human body based on Charge Coupled Devices (CCD) and infrared sensors is presented in this paper. The system can measure the bare size of human body that excludes the effect of clothing quickly and accurately.展开更多
The laser scanning and CCD image-transmitting measurement method and principle on acquiring 3-D curved surface shape data are discussed. Computer processing technique of 3-D curved surface shape(be called“ 3 - D surf...The laser scanning and CCD image-transmitting measurement method and principle on acquiring 3-D curved surface shape data are discussed. Computer processing technique of 3-D curved surface shape(be called“ 3 - D surface shape”for short) data is analysed. This technique in- cludes these concrete methods and principles such as data smoothing, fitting, reconstructing ,elimi- nating and so on. The example and result about computer processing of 3- D surface shape data are given .展开更多
In this paper we propose a novel method for building animation model of realhuman body from surface scanned data. The human model is represented by a triangular mesh anddescribed as a layered geometric model. The mode...In this paper we propose a novel method for building animation model of realhuman body from surface scanned data. The human model is represented by a triangular mesh anddescribed as a layered geometric model. The model consists of two layers: the control skeletongenerating body animation from motion capture data, and the simplified surface model providing anefficient representation of the skin surface shape. The skeleton is generated automatically fromsurface scanned data using the feature extraction, and then a point-to-line mapping is used to mapthe surface model onto the underlying skeleton. The resulting model enables real-time and smoothanimation by manipulation of the skeleton while maintaining the surface detail. Compared withearlier approach, the principal advantages of our approach are the automated generation of bodycontrol skeletons from the scanned data for real-time animation, and the automatic mapping andanimation of the captured human surface shape. The human model constructed in this work can be usedfor applications of ergonomic design, garment CAD, real-time simulating humans in virtual realityenvironment and so on.展开更多
Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design.The diversity of pose and shape of human body models and the semantic gap make landmarking a ...Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design.The diversity of pose and shape of human body models and the semantic gap make landmarking a challenging problem.Inthis paper,a learning-based method is proposed to locate landmarks on human body models by analyzing the relationship between geometric descriptors and semantic labels of landmarks.A shape alignmentalgorithm is proposed to align human body models to break symmetric ambiguity.A symmetry-awaredescriptor is proposed based on the structure of the human body models,which is robust to both pose and shape variations in human body models.AnAdaBoost regression algorithm is adopted to establish the correspondence between several descriptors and semantic labels of the landmarks.Quantitative and qualitative analyses and comparisons show that the proposed method can obtain more accurate landmarks and distinguish symmetrical landmarks semantically.Additionally,a dataset of landmarked human body models is also provided,containing 271 human body models collected from current human body datasets;each model has 17 landmarks labeled manually.展开更多
This paper describes a method of the computer aided garment design,and discusses 3-D humanbody,wire frame modelling,approaches of expressing and a shading model of the 3-D garment.
A 3-Dimensional computer aided garment design (CAGD) system has been developed andimplemented on a high-performance workstation. We studied various approaches to the func-tional modelling of garment designs for the sy...A 3-Dimensional computer aided garment design (CAGD) system has been developed andimplemented on a high-performance workstation. We studied various approaches to the func-tional modelling of garment designs for the system. According to the characteristic data of a hu-man body, the models of human body and the garment are displayed on the screen, then we canmodify the garment with various styles and different sizes. The system can transform the 3-Dgarment to the 2-D pieces. The system has improved design efficiency. Various potential alterna-tives and improvement of the system have also been studied and explored.展开更多
The safety production is critical to stable development of Chinese electric power industry. With the development of electric power enterprises, the requirements of its employees are also becoming higher and higher. In...The safety production is critical to stable development of Chinese electric power industry. With the development of electric power enterprises, the requirements of its employees are also becoming higher and higher. In this paper, an optical motion capture system based on the virtual reality technology is proposed to meet the requirements of the power enterprise for the qualified business ability. Electric power equipment, power equipment model entitative operating environment and the human model are established by electric power simulation unit, ZigBee technology and OpenGL graphics library. The problem of missing feature points is solved by applying the human model driven algorithm and the Kalman filtering algorithm. The experimental results show that it is more accurate to use Kalman filtering algorithm to extract the feature point in tracking process of actual motion capture and real-time animation display. The average absolute error of 3D coordinates is 1.61 mm and the average relative error is 2.23%. The system can improve trainees’ sense of experience and immersion.展开更多
基金supported by the Future Challenge Program through the Agency for Defense Development funded by the Defense Acquisition Program Administration (No.UC200015RD)。
文摘Swarm robot systems are an important application of autonomous unmanned surface vehicles on water surfaces.For monitoring natural environments and conducting security activities within a certain range using a surface vehicle,the swarm robot system is more efficient than the operation of a single object as the former can reduce cost and save time.It is necessary to detect adjacent surface obstacles robustly to operate a cluster of unmanned surface vehicles.For this purpose,a LiDAR(light detection and ranging)sensor is used as it can simultaneously obtain 3D information for all directions,relatively robustly and accurately,irrespective of the surrounding environmental conditions.Although the GPS(global-positioning-system)error range exists,obtaining measurements of the surface-vessel position can still ensure stability during platoon maneuvering.In this study,a three-layer convolutional neural network is applied to classify types of surface vehicles.The aim of this approach is to redefine the sparse 3D point cloud data as 2D image data with a connotative meaning and subsequently utilize this transformed data for object classification purposes.Hence,we have proposed a descriptor that converts the 3D point cloud data into 2D image data.To use this descriptor effectively,it is necessary to perform a clustering operation that separates the point clouds for each object.We developed voxel-based clustering for the point cloud clustering.Furthermore,using the descriptor,3D point cloud data can be converted into a 2D feature image,and the converted 2D image is provided as an input value to the network.We intend to verify the validity of the proposed 3D point cloud feature descriptor by using experimental data in the simulator.Furthermore,we explore the feasibility of real-time object classification within this framework.
基金This work was supported by the natural science foundation of Henan province(004061000)
文摘To realize the automation of fashion industry measuring,designing and manufacturing, the auto-measurement of 3D size of human body is of great importance. The auto measurement system of 3D human body based on Charge Coupled Devices (CCD) and infrared sensors is presented in this paper. The system can measure the bare size of human body that excludes the effect of clothing quickly and accurately.
文摘The laser scanning and CCD image-transmitting measurement method and principle on acquiring 3-D curved surface shape data are discussed. Computer processing technique of 3-D curved surface shape(be called“ 3 - D surface shape”for short) data is analysed. This technique in- cludes these concrete methods and principles such as data smoothing, fitting, reconstructing ,elimi- nating and so on. The example and result about computer processing of 3- D surface shape data are given .
文摘In this paper we propose a novel method for building animation model of realhuman body from surface scanned data. The human model is represented by a triangular mesh anddescribed as a layered geometric model. The model consists of two layers: the control skeletongenerating body animation from motion capture data, and the simplified surface model providing anefficient representation of the skin surface shape. The skeleton is generated automatically fromsurface scanned data using the feature extraction, and then a point-to-line mapping is used to mapthe surface model onto the underlying skeleton. The resulting model enables real-time and smoothanimation by manipulation of the skeleton while maintaining the surface detail. Compared withearlier approach, the principal advantages of our approach are the automated generation of bodycontrol skeletons from the scanned data for real-time animation, and the automatic mapping andanimation of the captured human surface shape. The human model constructed in this work can be usedfor applications of ergonomic design, garment CAD, real-time simulating humans in virtual realityenvironment and so on.
基金jointly supported by the National Natural Science Foundation of China under Grant Nos.61732015,61932018,and 61472349.
文摘Landmarks on human body models are of great significance for applications such as digital anthropometry and clothing design.The diversity of pose and shape of human body models and the semantic gap make landmarking a challenging problem.Inthis paper,a learning-based method is proposed to locate landmarks on human body models by analyzing the relationship between geometric descriptors and semantic labels of landmarks.A shape alignmentalgorithm is proposed to align human body models to break symmetric ambiguity.A symmetry-awaredescriptor is proposed based on the structure of the human body models,which is robust to both pose and shape variations in human body models.AnAdaBoost regression algorithm is adopted to establish the correspondence between several descriptors and semantic labels of the landmarks.Quantitative and qualitative analyses and comparisons show that the proposed method can obtain more accurate landmarks and distinguish symmetrical landmarks semantically.Additionally,a dataset of landmarked human body models is also provided,containing 271 human body models collected from current human body datasets;each model has 17 landmarks labeled manually.
文摘This paper describes a method of the computer aided garment design,and discusses 3-D humanbody,wire frame modelling,approaches of expressing and a shading model of the 3-D garment.
文摘A 3-Dimensional computer aided garment design (CAGD) system has been developed andimplemented on a high-performance workstation. We studied various approaches to the func-tional modelling of garment designs for the system. According to the characteristic data of a hu-man body, the models of human body and the garment are displayed on the screen, then we canmodify the garment with various styles and different sizes. The system can transform the 3-Dgarment to the 2-D pieces. The system has improved design efficiency. Various potential alterna-tives and improvement of the system have also been studied and explored.
文摘The safety production is critical to stable development of Chinese electric power industry. With the development of electric power enterprises, the requirements of its employees are also becoming higher and higher. In this paper, an optical motion capture system based on the virtual reality technology is proposed to meet the requirements of the power enterprise for the qualified business ability. Electric power equipment, power equipment model entitative operating environment and the human model are established by electric power simulation unit, ZigBee technology and OpenGL graphics library. The problem of missing feature points is solved by applying the human model driven algorithm and the Kalman filtering algorithm. The experimental results show that it is more accurate to use Kalman filtering algorithm to extract the feature point in tracking process of actual motion capture and real-time animation display. The average absolute error of 3D coordinates is 1.61 mm and the average relative error is 2.23%. The system can improve trainees’ sense of experience and immersion.
