Full-parallax light-field is captured by a small-scale 3D image scanning system and applied to holographic display. A vertical camera array is scanned horizontally to capture full-parallax imagery, and the vertical vi...Full-parallax light-field is captured by a small-scale 3D image scanning system and applied to holographic display. A vertical camera array is scanned horizontally to capture full-parallax imagery, and the vertical views between cameras are interpolated by depth image-based rendering technique. An improved technique for depth estimation reduces the estimation error and high-density light-field is obtained. The captured data is employed for the calculation of computer hologram using ray-sampling plane. This technique enables high-resolution display even in deep 3D scene although a hologram is calculated from ray information, and thus it makes use of the important advantage of holographic 3D display.展开更多
With the rapid advancement of artificial intelligence,research on enabling computers to assist humans in achieving intelligent augmentation-thereby enhancing the accuracy and efficiency of information perception and p...With the rapid advancement of artificial intelligence,research on enabling computers to assist humans in achieving intelligent augmentation-thereby enhancing the accuracy and efficiency of information perception and processing-has been steadily evolving.Among these developments,innovations in human motion capture technology have been emerging rapidly,leading to an increasing diversity in motion capture data types.This diversity necessitates the establishment of a unified standard for multi-source data to facilitate effective analysis and comparison of their capability to represent human motion.Additionally,motion capture data often suffer from significant noise,acquisition delays,and asynchrony,making their effective processing and visualization a critical challenge.In this paper,we utilized data collected from a prototype of flexible fabric-based motion capture clothing and optical motion capture devices as inputs.Time synchronization and error analysis between the two data types were conducted,individual actions from continuous motion sequences were segmented,and the processed results were presented through a concise and intuitive visualization interface.Finally,we evaluated various system metrics,including the accuracy of time synchronization,data fitting error from fabric resistance to joint angles,precision of motion segmentation,and user feedback.展开更多
To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic ...To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.展开更多
基金partly supported by the JSPS Grant-in-Aid for Scientific Research #17300032
文摘Full-parallax light-field is captured by a small-scale 3D image scanning system and applied to holographic display. A vertical camera array is scanned horizontally to capture full-parallax imagery, and the vertical views between cameras are interpolated by depth image-based rendering technique. An improved technique for depth estimation reduces the estimation error and high-density light-field is obtained. The captured data is employed for the calculation of computer hologram using ray-sampling plane. This technique enables high-resolution display even in deep 3D scene although a hologram is calculated from ray information, and thus it makes use of the important advantage of holographic 3D display.
基金supported by National Natural Science Foun-dation of China(62072383,61702433)the Public Technology Service Platform Project of Xiamen City(No.3502Z20231043)+2 种基金Xiaomi Young Talents Program/Xiaomi Foundation,the Funda-mental Research Funds for the Central Universities,Chinasupported by National Natural Science Founda-tion of China(62077039)the Fundamental Research Funds for the Central Universities,China(20720230106).
文摘With the rapid advancement of artificial intelligence,research on enabling computers to assist humans in achieving intelligent augmentation-thereby enhancing the accuracy and efficiency of information perception and processing-has been steadily evolving.Among these developments,innovations in human motion capture technology have been emerging rapidly,leading to an increasing diversity in motion capture data types.This diversity necessitates the establishment of a unified standard for multi-source data to facilitate effective analysis and comparison of their capability to represent human motion.Additionally,motion capture data often suffer from significant noise,acquisition delays,and asynchrony,making their effective processing and visualization a critical challenge.In this paper,we utilized data collected from a prototype of flexible fabric-based motion capture clothing and optical motion capture devices as inputs.Time synchronization and error analysis between the two data types were conducted,individual actions from continuous motion sequences were segmented,and the processed results were presented through a concise and intuitive visualization interface.Finally,we evaluated various system metrics,including the accuracy of time synchronization,data fitting error from fabric resistance to joint angles,precision of motion segmentation,and user feedback.
基金Project(60801053) supported by the National Natural Science Foundation of ChinaProject(4082025) supported by the Beijing Natural Science Foundation,China+4 种基金Project(20070004037) supported by the Doctoral Foundation of ChinaProject(2009JBM135,2011JBM023) supported by the Fundamental Research Funds for the Central Universities of ChinaProject(151139522) supported by the Hongguoyuan Innovative Talent Program of Beijing Jiaotong University,ChinaProject(YB20081000401) supported by the Beijing Excellent Doctoral Thesis Program,ChinaProject (2006CB303105) supported by the National Basic Research Program of China
文摘To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.
