Study on the Application of UWB Positioning Technology in Multiplayer Mechanical Motion Capture System

2013 ◽  
Vol 416-417 ◽  
pp. 1341-1345 ◽  
Author(s):  
Guang Tian Shi ◽  
Shuai Li
Keyword(s):  
Motion Capture ◽  
Human Body ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Motion Capture System ◽  
Mechanical Motion ◽  
Motion Data ◽  
Positioning Technique ◽  
Coordinate Data ◽  
Three Dimensional Space

Because the mechanical motion capture system can only capture the motion data of the human body and it can`t achieve the positioning function in three-dimensional space, therefore, it is only suitable for capturing just one person's motion data. This paper will introduce the UWB positioning technology to the multiplayer mechanical motion capture system, the system through the mechanical motion capture technology to get the motion data of performers and using UWB positioning technique to obtain the coordinate data of each performer, then through the integration and calculation of the above two kinds of data, the system will acquire the complete motion data of each performer.

scholarly journals Cloth Simulation with Adaptive Force Model in Three-Dimensional Space

2018 ◽  
Vol 13 (1) ◽  
pp. 155892501801300
Author(s):  
Xuan Luo ◽  
Gaoming Jiang ◽  
Honglian Cong ◽  
Yan Zhao
Keyword(s):  
Human Body ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Mathematical Expression ◽  
Experimental Results ◽  
Force Model ◽  
Mathematical Form ◽  
Cloth Simulation ◽  
3D Space ◽  
Three Dimensional Space

An adaptive force model is proposed to achieve better performance between the accuracy and the speed of cloth simulation in three-dimensional (3D) space. The proposed force model can be expressed with a general mathematical form demonstrated by the distance between the clothing and the human body. This paper defines how a continuous adaptive area can be established with a shape “block”. It is clarified that, within a specific block, a force model is expressed with the gravity of the clothing, the forces of the adjacent blocks and the anti-force of the human body to the block. In this manner, the force model of the desired clothing can be obtained through a general mathematical expression. The simulations and experimental results demonstrate that the acceptable clothing simulation in 3D space can be achieved with higher speed by saving about 20.2% runtime, and the efficiency of the proposed scheme can be verified.

scholarly journals Extraction of Human Motion Information from Digital Video Based on 3D Poisson Equation

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yilin Wang ◽  
Baokuan Chang
Keyword(s):  
Poisson Equation ◽  
Human Body ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Feature Space ◽  
Human Motion ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Dimensional Space Time ◽  
Three Dimensional Space

Based on the 3D Poisson equation, this paper extracts the features of the digital video human body action sequence. By solving the Poisson equation on the silhouette sequence, the time and space features, time and space structure features, shape features, and orientation features can be obtained. First, we use the silhouette structure features in three-dimensional space-time and the orientation features of the silhouette in three-dimensional space-time to represent the local features of the silhouette sequence and use the 3D Zernike moment feature to represent the overall features of the silhouette sequence. Secondly, we combine the Bayesian classifier and AdaBoost classifier to learn and classify the features of human action sequences, conduct experiments on the Weizmann video database, and conduct multiple experiments using the method of classifying samples and selecting partial combinations for training. Then, using the recognition algorithm of motion capture, after the above process, the three-dimensional model is obtained and matched with the model in the three-dimensional model database, the sequence with the smallest distance is calculated, and the corresponding skeleton is outputted as the results of action capture. During the experiment, the human motion tracking method based on the university matching kernel (EMK) image kernel descriptor was used; that is, the scale invariant operator was used to count the characteristics of multiple training images, and finally, the high-dimensional feature space was mapped into the low-dimensional to obtain the feature space approximating the Gaussian kernel. Based on the above analysis, the main user has prior knowledge of the network environment. The experimental results show that the method in this paper can effectively extract the characteristics of human body movements and has a good classification effect for bending, one-foot jumping, vertical jumping, waving, and other movements. Due to the linear separability of the data in the kernel space, fast linear interpolation regression is performed on the features in the feature space, which significantly improves the robustness and accuracy of the estimation of the human motion pose in the image sequence.

Three-Dimensional Profiles of Movements of Human Body Joint Centers

1975 ◽  
Vol 19 (4) ◽  
pp. 394-402
Author(s):  
S. Deivanayagam ◽  
M.M. Ayoub ◽  
Kenneth Kennedy
Keyword(s):  
Human Body ◽  
Shoulder Joint ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Computer Models ◽  
Body Joint ◽  
Three Dimensional Space

Certain results of an experimental ingestigation on motion profiles, in three-dimensional space for various body landmarks while the hand moves from one location to another are presented here. Grip, wrist, elbow and shoulder joint centers were of primary consideration for this study. A photogrammetric technique was adopted to record the movement and to extract the required information later. Seven subjects participated and 30 movements were performed by each of them under three different seat configurations and six controller locations. This research was initiated for the purpose of developing computer models in aircraft cockpits.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

A Peptoid with Extended Shape in Water

2019 ◽  
Author(s):  
Jumpei Morimoto ◽  
Yasuhiro Fukuda ◽  
Takumu Watanabe ◽  
Daisuke Kuroda ◽  
Kouhei Tsumoto ◽  
...  
Keyword(s):  
Spectroscopic Analysis ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Biomolecular Recognition ◽  
Biological Application ◽  
New Class ◽  
Proteolytic Resistance ◽  
Pharmacokinetic Properties ◽  
Optically Pure ◽  
Three Dimensional Space

<div> <div> <div> <p>“Peptoids” was proposed, over decades ago, as a term describing analogs of peptides that exhibit better physicochemical and pharmacokinetic properties than peptides. Oligo-(N-substituted glycines) (oligo-NSG) was previously proposed as a peptoid due to its high proteolytic resistance and membrane permeability. However, oligo-NSG is conformationally flexible and is difficult to achieve a defined shape in water. This conformational flexibility is severely limiting biological application of oligo-NSG. Here, we propose oligo-(N-substituted alanines) (oligo-NSA) as a new peptoid that forms a defined shape in water. A synthetic method established in this study enabled the first isolation and conformational study of optically pure oligo-NSA. Computational simulations, crystallographic studies and spectroscopic analysis demonstrated the well-defined extended shape of oligo-NSA realized by backbone steric effects. The new class of peptoid achieves the constrained conformation without any assistance of N-substituents and serves as an ideal scaffold for displaying functional groups in well-defined three-dimensional space, which leads to effective biomolecular recognition. </p> </div> </div> </div>

scholarly journals Quantitative image analysis of microbial communities with BiofilmQ

2021 ◽  
Author(s):  
Raimo Hartmann ◽  
Hannah Jeckel ◽  
Eric Jelli ◽  
Praveen K. Singh ◽  
Sanika Vaidya ◽  
...  
Keyword(s):  
Image Analysis ◽  
Microbial Communities ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Software Tool ◽  
Image Cytometry ◽  
Quantitative Image Analysis ◽  
Space And Time ◽  
Quantitative Image ◽  
Three Dimensional Space

AbstractBiofilms are microbial communities that represent a highly abundant form of microbial life on Earth. Inside biofilms, phenotypic and genotypic variations occur in three-dimensional space and time; microscopy and quantitative image analysis are therefore crucial for elucidating their functions. Here, we present BiofilmQ—a comprehensive image cytometry software tool for the automated and high-throughput quantification, analysis and visualization of numerous biofilm-internal and whole-biofilm properties in three-dimensional space and time.

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