Gourd pyrography art simulating based on non-photorealistic rendering

Qian, Wei; Xu, Dan; Yue, Kun; Guan, Zheng; Pu, Yuanyuan; Shi, Yongjie

doi:10.1007/s11042-016-3801-8

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…e study of di usion of di erent pigments was presented by [9], but did not really address the di usion and superimposition e ects of di erent pigments. Only a single KM colour model was used to simulate the colour of different pigments.…”

Section: Introductionmentioning

confidence: 99%

Analysis on the Artistic Presentation Effect of 3D Rendering Ink Painting Based on the Evaluation of Deep Learning Model

Pan

2022

Scientific Programming

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At present, with the popularity of multimedia, people's appreciation and interest in ink painting art have been deepened. In the research of art works, this paper proposes a rendering method of three-dimensional ink painting effect based on deep learning model, which can simulate the painting skills of ink painting in terms of intensity and distance. Specifically, first construct a two-dimensional ink texture, then map the horizontal component of the texture using the contour information of the model, and finally adjust the ink tone by controlling the coordinates of the vertical component of the texture through the attribute function. Linear attribute function, quadratic attribute function, and attribute function with light source factor are used for simulation. The results show that this method can be used for ink and wash simulation of three-dimensional scene, making the image more layered and more in line with the artist’s actual technology.

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Section: Introductionmentioning

confidence: 99%

Analysis on the Artistic Presentation Effect of 3D Rendering Ink Painting Based on the Evaluation of Deep Learning Model

Pan

2022

Scientific Programming

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“…Currently, with the development of video games and animated movies, non-realistic rendering technology is attracting increasing attention. Many relevant research studies have been reported and many algorithms have been proposed that achieve a satisfactory visual effect [29]- [34]. In [32], Liang et al proposed a method for automatically stylizing portrait videos that contain small human faces that extends the mask regions with the convolutional neural network (R-CNN) features.…”

Section: Related Workmentioning

confidence: 99%

Parallel Fast Pencil Drawing Generation Algorithm Based on GPU

Qiu

Liu

et al. 2019

IEEE Access

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With the development of image processing technology, pencil drawing has been widely used in video games and mobile phone applications. However, the existing pencil drawing algorithms require a large amount of time to convert a real picture into a pencil drawing; hence, it is difficult to apply them to real-time systems. This paper proposes a parallel fast pencil drawing generation algorithm based on the graphics processing unit (GPU) to accelerate the real-time rendering process of sketch painting. The parallelism of the pencil drawing generation algorithm is identified via a theoretical analysis at first. Then, sub-algorithms of the sequential algorithm are designed in parallel using the compute unified device architecture (CUDA) programming model and executed via thread-level parallel techniques. Furthermore, an optimal cache pattern of data that reduce the access time of the most frequently used data is structured using shared memory and constant memory. Finally, task-level parallelism is achieved by the CUDA stream technology, which overlaps independent sub-tasks for further acceleration. On the CUDA platform, the experimental results demonstrate that the proposed parallel algorithm can achieve a significant increase in speedup. The proposed algorithm achieves a performance improvement of 448.59 times compared with the sequential algorithm, on 2560×1920-resolution images, and maintains a high degree of similarity with the real pencil paintings. Hence, the proposed algorithm is suitable for real-time pencil drawing rendering and has promising application prospects in non-photorealistic rendering. INDEX TERMS Non-photorealistic rendering, pencil drawing, parallel algorithm, GPU platform, convolution operation, CUDA.

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“…Non-photorealistic rendering is a field of computer graphics that can generate effective illustrations and attractive artistic images. Some researchers have proposed non-photorealistic rendering methods to simulate art expression techniques and to develop unprecedented artistic approaches [1][2][3][4][5][6][7]. One of the unprecedented artistic approaches is a method to generating cell-like images by an iterative calculation using inverse iris filter from photographic images [8].…”

Section: Introductionmentioning

confidence: 99%

Generation of Cell-Like Images Using Euclidean Distance from Edge

Hiraoka¹,

Maeda²

2021

JRNAL

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A non-photorealistic rendering method has been proposed to generate cell-like images in which cell-like patterns are represented in photographic images. Cell-like patterns are automatically generated by the change of density of photographic images. However, cell-like patterns are irregularly arranged. In this paper, we propose a method to arrange cell-like patterns along the edges of photographic images. In addition, our method can express cell membrane and cell nucleus in cell-like patterns more clearly than the conventional method. We improves the conventional method by using Euclidean distance from the edges. We show that appealing cell-like images can be generated by our method through experiments using various photographic images.

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Gourd pyrography art simulating based on non-photorealistic rendering

Cited by 7 publications

References 25 publications

Analysis on the Artistic Presentation Effect of 3D Rendering Ink Painting Based on the Evaluation of Deep Learning Model

Analysis on the Artistic Presentation Effect of 3D Rendering Ink Painting Based on the Evaluation of Deep Learning Model

Parallel Fast Pencil Drawing Generation Algorithm Based on GPU

Generation of Cell-Like Images Using Euclidean Distance from Edge

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