scholarly journals Design of Sanda Action Reconstruction Model Based on 3D Images

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Hongwei Zhao
Keyword(s):  
Image Reconstruction ◽  
Digital Image ◽  
Corner Detection ◽  
Reconstruction Method ◽  
Feature Points ◽  
3D Image ◽  
Phase Compensation ◽  
3D Image Reconstruction ◽  
Compensation Methods ◽  
Digital Frame

In order to improve the training level of Sanda movement, this article uses an image analysis method to reconstruct the detailed characteristics of the movement and apply them to the actual training process. Since the traditional wavelet reconstruction method is affected by the accuracy of the decomposition scale, this paper proposes an improved method of Sanda action based on 3D image reconstruction. First, the method relies on frame adjacent phase compensation and digital image stabilization techniques to perform digital frame operations on the image. Then, scanning and corner detection are used for image reconstruction, where adjacent phase compensation methods are used to match feature points and gray pixels. Image extraction is performed by extracting key feature points of the action 3D image, and a fast frame detection method is used to stabilize the image of the digital image, thereby improving the image quality of image reconstruction. The experimental results show that the method has good image output effect and has a high application value in Sanda guidance and optimization.

scholarly journals Simulation of 3D Image Reconstruction in Rigid body Motion

2018 ◽  
Vol 232 ◽  
pp. 02002
Author(s):  
Huihong Chen ◽  
Shiming Li
Keyword(s):  
Image Reconstruction ◽  
Rigid Body ◽  
Rigid Body Motion ◽  
Corner Detection ◽  
Body Motion ◽  
3D Image ◽  
3D Images ◽  
3D Image Reconstruction ◽  
Contour Feature

3D image reconstruction under rigid body motion is affected by rigid body motion and visual displacement factors, which leads to low quality of 3D image reconstruction and more noise, in order to improve the quality of 3D image reconstruction of rigid body motion. A 3D image reconstruction technique is proposed based on corner detection and edge contour feature extraction in this paper. Region scanning and point scanning are combined to scan rigid body moving object image. The wavelet denoising method is used to reduce the noise of the 3D image. The edge contour feature of the image is extracted. The sparse edge pixel fusion method is used to decompose the feature of the 3D image under the rigid body motion. The irregular triangulation method is used to extract and reconstruct the information features of the rigid body 3D images. The reconstructed feature points are accurately calibrated with the corner detection method to realize the effective reconstruction of the 3D images. The simulation results show that the method has good quality, high SNR of output image and high registration rate of feature points of image reconstruction, and proposed method has good performance of 3D image reconstruction.

scholarly journals Research on the Application of Visual Sensing Technology in Art Education

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenli Mao ◽  
Bingyu Zhang
Keyword(s):  
Image Reconstruction ◽  
Art Education ◽  
Digital Image ◽  
Visual Communication ◽  
3D Image ◽  
Reconstruction Accuracy ◽  
Visual Sensing ◽  
3D Image Reconstruction ◽  
Image Layer ◽  
Sensing Technology

It is essential to have a new understanding of the development of visual sensing technology in digital image art at this stage, in order to make traditional art education have new professional ability teaching. Based on the current research results in related fields, a three-dimensional (3D) image visual communication system based on digital image automatic reconstruction is proposed with two schemes as the premise. In scheme 1, the hardware part is divided into two modules. The hardware used by the analysis of the 3D image layer module is the HUJ-23 3D image processor. The acquisition of a 3D image layer module uses the hardware of a realistic infrared camera. The software of the system consists of two parts: a 3D image computer expression module and a 3D image reconstruction module. A simulation platform is established. The test data of 3D image reconstruction accuracy and visual communication integrity of the designed system show that both of them show a good trend. In scheme 2, regarding digital image processing, the 3D image visual perception reconstruction is affected by the modeling conditions, and some images are incomplete and damaged. The depth camera and image processor that can be used in the visual communication technology are selected, and their internal parameters are modified to borrow them in the original system hardware. Gaussian filtering model combined with scale-invariant feature transform (SIFT) feature point extraction algorithm is adopted to select image feature points. Previous system reconstruction technology is used to upgrade the 3D digital image, and the feature point detection equation is adopted to detect the accuracy of the upgraded results. Based on the above hardware and software research, the 3D digital image system based on visual communication is successfully upgraded. The test platform is established, and the test samples are selected. Unlike the previous systems, the 3D image reconstruction accuracy of the designed visual communication system can be as high as 98%; the upgraded system has better image integrity and stronger performance than the previous systems and achieves higher visual sensing technology. In art education, it can provide a new content perspective for digital image art teaching.

FAST RECONSTRUCTION METHOD BASED ON COMMON UNIFIED DEVICE ARCHITECTURE (CUDA) FOR MICRO-CT

2010 ◽  
Vol 03 (01) ◽  
pp. 39-43 ◽  
Author(s):  
GUOTAO QUAN ◽  
TANGYOU SUN ◽  
YONG DENG
Keyword(s):  
Image Reconstruction ◽  
Graphics Processing Units ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Micro Ct ◽  
3D Image ◽  
Reconstruction Process ◽  
Device Architecture ◽  
3D Image Reconstruction ◽  
Fdk Algorithm

Three-dimensional image reconstruction with Feldkamp, Davis, and Kress (FDK) algorithm is the most time consuming part in Micro-CT. The parallel algorithm based on the computer cluster is capable of accelerating image reconstruction speed; however, the hardware is very expensive. In this paper, using the most current graphics processing units (GPU), we present a method based on common unified device architecture (CUDA) for speeding up the Micro-CT image reconstruction process. The most time consuming filtering and back-projection parts of the FDK algorithm are parallelized for the CUDA architecture. The CUDA-based reconstruction speed and image qualities are compared with CPU results for the projecting data of the Micro-CT system. The results show that the 3D image reconstruction speed based on CUDA is ten times faster than the speed with CPU. In conclusion the FDK algorithm based on CUDA for Micro-CT can reconstruct the 3D image right after the end of data acquisition.

scholarly journals A new solution to the curved Ewald sphere problem for 3D image reconstruction in electron microscopy

2021 ◽  
Vol 224 ◽  
pp. 113234
Author(s):  
J.P.J. Chen ◽  
K.E. Schmidt ◽  
J.C.H. Spence ◽  
R.A. Kirian
Keyword(s):  
Electron Microscopy ◽  
Image Reconstruction ◽  
3D Image ◽  
3D Image Reconstruction ◽  
Ewald Sphere
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