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.

The Fast Three-Dimensional Space-Time Neutron Kinetic Model for Cartesian Geometry and Cylindrical Geometry

2016 ◽  
Author(s):  
Zhifeng Li ◽  
Hongchun Wu ◽  
Chenghui Wan ◽  
Tianliang Hu
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Space Time ◽  
Cylindrical Geometry ◽  
Neutron Diffusion ◽  
Diffusion Kinetics ◽  
Dimensional Space Time ◽  
Cartesian Geometry ◽  
Predictor Corrector ◽  
Three Dimensional Space

In order to raise computation speed on the premise of enough numerical accuracy, the Predictor-Corrector Improved Quasi-Static (PC-IQS) method and Nodal Green’s Function Method (NGFM) were combined to solve the three-dimensional space-time neutron diffusion kinetics problems for Cartesian geometry. In addition, the improved quasi-static method and the Krylov algorithm were applied to solve the three-dimensional space-time neutron diffusion kinetics problems for cylindrical geometry. Based on the proposed model, the program of three-dimensional neutron space-time kinetic code has been tested by the two-dimensional and three-dimensional transient numerical benchmarks. The numerical results obtained by this work were in good agreement with the reference solutions.

scholarly journals ANIMATED THREE-DIMENSIONAL MODEL OF THE AMUR COSSACK OF THE XVII CENTURY

2021 ◽  
pp. 58-62
Author(s):  
VLADISLAV ROMANOVICH MOSKALCHUK ◽  
◽  
KIRILL NIKOLAEVICH TARASENKO ◽  
Keyword(s):  
Human Body ◽  
Three Dimensional ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Xvii Century ◽  
Polygonal Model

The stages of modeling a historically accurate character are considered, from recreating the human body and clothing from sketches to optimizing and baking a highly polygonal model onto a texture.

Large-scale dynamics in turbulent mixing and the three-dimensional space–time behaviour of outer fluid interfaces

2002 ◽  
Vol 471 ◽  
pp. 381-408 ◽  
Author(s):  
HARIS J. CATRAKIS ◽  
ROBERTO C. AGUIRRE ◽  
JESUS RUIZ-PLANCARTE ◽  
ROBERT D. THAYNE ◽  
BRENDA A. McDONALD ◽  
...  
Keyword(s):  
Large Scale ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Space Time ◽  
Mixing Efficiency ◽  
Fluid Interfaces ◽  
Ambient Fluid ◽  
Wide Range ◽  
Dimensional Space Time ◽  
Three Dimensional Space

Experiments have been conducted to investigate turbulent mixing and the dynamics of outer fluid interfaces, i.e. the interfaces between mixed fluid and pure ambient fluid. A novel six-foot-diameter octagonal-tank flow facility was developed to enable the optical imaging of fluid interfaces above the mixing transition, corresponding to fully developed turbulence. Approximately 10003 whole-field three-dimensional space– time measurements of the concentration field were recorded using laser-induced- fluorescence digital-imaging techniques in turbulent jets at a Reynolds number of Re ∼ 20 000, Schmidt number of Sc ∼ 2000, and downstream distance of ∼ 500 nozzle diameters. Multiple large-scale regions of spatially nearly uniform-concentration fluid are evident in instantaneous visualizations, in agreement with previous findings above the mixing transition. The ensemble-averaged probability density function of concentration is found to exhibit linear dependence over a wide range of concentration thresholds. This can be accounted for in terms of the dynamics of large-scale well- mixed regions. Visualization of the three-dimensional space–time concentration field indicates that molecular mixing of entrained pure ambient fluid is dynamically initiated and accomplished in the vicinity of the unsteady large scales. Examination of the outer interfaces shows that they are dynamically confined primarily near the instantaneous large-scale boundaries of the flow. This behaviour is quantified in terms of the probability density of the location of the outer interfaces relative to the flow centreline and the probability of pure ambient fluid as a function of distance from the centreline. The current measurements show that the dynamics of outer interfaces above the mixing transition is significantly different from the behaviour below the transition, where previous studies have shown that unmixed ambient fluid can extend across a wide range of transverse locations in the flow interior. The present observations of dynamical confinement of the outer interfaces to the unsteady large scales, and considerations of entrainment, suggest that the mechanism responsible for this behaviour must be the coupling of large-scale flow dynamics with the presence of small-scale structures internal to the large-scale structures, above the mixing transition. The dynamics and structure of the outer interfaces across the entire range of space–time scales are quantified in terms of a distribution of generalized level-crossing scales. The outer-interface behaviour determines the mixing efficiency of the flow, i.e. fraction of mixed fluid. The present findings indicate that the large-scale dynamics of the outer interfaces above the mixing transition provides the dominant contribution to the mixing efficiency. This suggests a new way to quantify the mixing efficiency of turbulent flows at high Reynolds numbers.

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