A 3D graphics rendering pipeline implementation based on the openCL massively parallel processing

Kim, Mingyu; Baek, Nakhoon

doi:10.1007/s11227-020-03581-8

Cited by 11 publications

(4 citation statements)

References 33 publications

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“…It developed some special features for the efficient rendering, even in a single pass rendering, with CUDA atomic operations. It shows good performance for small-size objects, while the CUDARaster [10] and its followers [11], [12], [13] are also software 3D graphics rendering pipeline implementations, with CUDA. CUDARaster was implemented for a specific CUDA model of Fermi, and it also uses some assembly-level codes, for optimization purpose.…”

Section: Previous Workmentioning

confidence: 99%

A Prototype Implementation of a CUDA-based Customized Rasterizer

Baek¹

2022

IJACSA

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In these days, we have high-performance massively parallel computing devices, as well as high-performance 3D graphics rendering devices. In this paper, we show a prototype implementation of a full-software 3D rasterizer system, based on the CUDA parallel architecture. While most of previous CUDAbased software rasterizer implementations focused on the triangle primitives, our system includes more 3D primitives, and extra 2D primitives, to fully support 3D graphics library features. Currently, our system is at its prototype implementation stage, and it shows successful results with 3D primitive handling and also character output features. Our design and implementation details are presented. More optimizations and fine tunes will be followed in near future.

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Section: Previous Workmentioning

confidence: 99%

A Prototype Implementation of a CUDA-based Customized Rasterizer

Baek¹

2022

IJACSA

Self Cite

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“…According to the fitting method above, it is easy to get more pictures of the relevant results quickly and to segment these pictures to make a picture resource library. The surface segmentation shader in the Unity engine rendering pipeline 24,25 is used to achieve two types of personalized fitting, one for different body sizes and one for different clothing sizes.…”

Section: Personalized Try-onmentioning

confidence: 99%

Two‐dimensional virtual try‐on algorithm and application research for personalized dressing

Chen

et al. 2022

Int J of Intelligent Sys

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To reduce the cost of virtual try‐on, a method of image deformation by body part size is proposed for the traditional two‐dimensional virtual try‐on method, which is challenging to represent the personalized characteristics of the body size of the fitting subject. On the basis of the input information of the user's body size, the method can generate a fitting effect that shows the user's characteristics with the corresponding clothes. The image segmentation algorithm is used to snap out the garment from the background garment image, and then the size and position of the garment are adjusted according to the dressing position of the standard mannequin image and fit the mannequin image. The final mesh with dense vertices is generated using surface subdivision. The experimental results show that this method can show good results in user personalized try‐on.

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“…Commonly referred to as a rendering pipeline, it is a series of data processing for application's data into the final rendering of an image [10]. e rendering process is shown in Figure 1.…”

Section: Graphical Rendering Processmentioning

confidence: 99%

Research on Visual Image Texture Rendering for Artistic Aided Design

Xiao

2021

Scientific Programming

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The rendering effect of known visual image texture is poor and the output image is not always clear. To solve this problem, this paper proposes a visual image rendering based on scene visual understanding algorithm. In this approach, the color segmentation of known visual scene is carried out according to a predefined threshold, and the segmented image is processed by morphology. For this purpose, the extraction rules are formulated to screen the candidate regions. The color image is fused and filtered in the neighborhood, the pixels of the image are extracted, and the 2D texture recognition is realized by multilevel fusion and visual feature reconstruction. Using compact sampling to extract more target features, feature points are matched, the coordinate system of known image information are integrated into a unified coordinate system, and design images are generated to complete art-aided design. Simulation results show that the proposed method is more accurate than the original method for extracting the information of known images, which helps to solve the problem of clearly visible output images and improves the overall design effect.

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A 3D graphics rendering pipeline implementation based on the openCL massively parallel processing

Cited by 11 publications

References 33 publications

A Prototype Implementation of a CUDA-based Customized Rasterizer

A Prototype Implementation of a CUDA-based Customized Rasterizer

Two‐dimensional virtual try‐on algorithm and application research for personalized dressing

Research on Visual Image Texture Rendering for Artistic Aided Design

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