Application of network protocol improvement and image content search in mathematical calculus 3D modeling video analysis

Wang, Xuqin

doi:10.1016/j.aej.2021.02.030

Cited by 9 publications

(3 citation statements)

References 19 publications

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“…Solve the triangular error matrix related to the point; the error matrix 𝑄 𝑖 about the point 𝑣 𝑖0 can be obtained [10].…”

Section: Detailed Selection Of the Modelmentioning

confidence: 99%

Application and Optimization of Mesh Simplification in 3D virtual Reality Scene in a High-performance Environment

He,

Wang,

Zhu

et al. 2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

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Real-time 3D imaging and display technology in virtual reality technology has become a key research object; However, modern computer work has been dramatically improved compared with the past; it still cannot meet the requirements of drawing realtime complex scenes and objects. Level of detail modeling technology is the most promising technology for 3D images, which is to develop a set of models with different levels of polygonal information from the same original model describing an event or object. Based on the above background, this article puts forward the application of 3D modelingbased LOD technology in virtual reality as the research goal, studies the concept of LOD technology in detail, analyzes the QEM algorithm, and then researches and optimizes the QEM algorithm. According to the experimental research in this article, the basic algorithm used in simplifying the initial model can simplify the model to a certain extent, but the data could be better. Using an immune genetic algorithm to facilitate nodes has succeeded dramatically, saving nearly 50% of nodes and about 90% of the time based on the most straightforward optimization. However, in this case, the model cannot display details.

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“…Solve the triangular error matrix related to the point; the error matrix 𝑄 𝑖 about the point 𝑣 𝑖0 can be obtained [10].…”

Section: Detailed Selection Of the Modelmentioning

confidence: 99%

Application and Optimization of Mesh Simplification in 3D virtual Reality Scene in a High-performance Environment

He,

Wang,

Zhu

et al. 2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

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show abstract

“…To address the problem of excessive resources occupied by the filter module, a hardware structure with a maximum 9 × 9 template based on a tree structure is proposed, which greatly solves the problem of excessive resource occupation. The hue mapping algorithm with halo reduction filter is implemented on FPGA, and functions such as adaptive parameter estimation and Gaussian-based halo reduction filter are accomplished [11]. An FPGA implementation of an infrared image enhancement algorithm with a combination of bilateral filtering and histogram equalization is proposed for infrared images.…”

Section: Related Workmentioning

confidence: 99%

Multifeature Contrast Enhancement Algorithm for Digital Media Images Based on the Diffusion Equation

Wang

Yuan

2022

Advances in Mathematical Physics

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This paper studies the processing of digital media images using a diffusion equation to increase the contrast of the image by stretching or extending the distribution of luminance data of the image to obtain clearer information of digital media images. In this paper, the image enhancement algorithm of nonlinear diffusion filtering is used to add a velocity term to the diffusion function using a coupled denoising model, which makes the diffusion of the original model smooth, and the interferogram is solved numerically with the help of numerical simulation to verify the denoising processing effect before and after the model correction. To meet the real-time applications in the field of video surveillance, this paper focuses on the optimization of the algorithm program, including software pipeline optimization, operation unit balancing, single instruction multiple data optimization, arithmetic operation optimization, and onchip storage optimization. These optimizations enable the nonlinear diffusion filter-based image enhancement algorithm to achieve high processing efficiency on the C674xDSP, with a processing speed of 25 posts per second for 640 × 480 size video images. Finally, the significance means a value of super pixel blocks is calculated in superpixel units, and the image is segmented into objects and backgrounds by combining with the Otsu threshold segmentation algorithm to mention the image. In this paper, the proposed algorithm experiments with several sets of Kor Kor resolution remote sensing images, respectively, and the Markov random field model and fully convolutional network (FCN) algorithm are used as the comparison algorithm. By comparing the experimental results qualitatively and quantitatively, it is shown that the algorithm in this paper has an obvious practical effect on contrast enhancement of digital media images and has certain practicality and superiority.

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“…Moreover, to meet the needs of different teaching scenarios, related research work must be optimized and improved for the specific issues of the education field [11,12]. This includes how to better capture and understand the key features of teaching content, and how to achieve efficient, realtime visual rendering to ensure the interactive experience in the educational environment [13,14]. Therefore, in-depth research on the application of 3D image modeling and visual presentation technologies in education is of significant practical importance.…”

Section: Introductionmentioning

confidence: 99%

3D Image Modeling and Visual Presentation Technologies for Education

Wang,

Yin,

Zhu

et al. 2024

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With the extensive application of digital media and interactive technologies in the field of education, 3D image modeling and visual presentation technologies have become key tools for enhancing the learning experience. These technologies can concretize abstract educational content, assisting students in understanding complex knowledge through intuitive means. Although current 3D modeling and rendering technologies are widely applied in education, existing methods still need improvement in feature extraction, model expressiveness, and rendering efficiency, particularly in meeting the demands for real-time interaction and providing immersive learning experiences. Addressing this issue, this paper delves into 3D educational image modeling methods based on inter-layer feature learning and explores visual rendering optimization strategies for 3D educational image scenes. By improving the capability of deep learning models to process educational content and optimizing the rendering process to support real-time interaction in large-scale scenes, this research aims to provide more accurate and efficient teaching tools, thereby enhancing the efficiency and quality of teaching and learning. The results indicate that the proposed methods significantly improve model detailing and rendering speed while ensuring visual effects, offering substantial practical significance in enhancing interactivity and immersion in educational technology.

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Application of network protocol improvement and image content search in mathematical calculus 3D modeling video analysis

Cited by 9 publications

References 19 publications

Application and Optimization of Mesh Simplification in 3D virtual Reality Scene in a High-performance Environment

Application and Optimization of Mesh Simplification in 3D virtual Reality Scene in a High-performance Environment

Multifeature Contrast Enhancement Algorithm for Digital Media Images Based on the Diffusion Equation

3D Image Modeling and Visual Presentation Technologies for Education

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