A Natural Image Pointillism with Controlled Ellipse Dots

Chi, Dongxiang

doi:10.1155/2014/567846

Cited by 4 publications

(3 citation statements)

References 33 publications

(61 reference statements)

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“…In this work, to obtain high‐quality tile art images, we generate a tile art image such that the total error is minimized, while several studies, which tackle tile art image generation, consider features in the original image such as edges and directions of gradation 10–12 . Unlike these studies, our proposed approach can represent such features without any image feature extraction techniques.…”

Section: Introductionmentioning

confidence: 99%

Tile art image generation using parallel greedy algorithm on the GPU and its approximation with machine learning

Matsumura

Tokura

Kuroda

et al. 2019

Concurrency and Computation

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Tile art image generation is one of the non-photorealistic rendering methods. The generated digital image resembles artistic representation given digital photos and illustrations. The first contribution of this paper is to propose a tile image generation based on the greedy approach.The greedy approach is based on the characteristic of the human visual system to optimize generated images. In addition, to shorten the computation time, we show the parallel algorithm and its GPU acceleration technique. We have implemented it on NVIDIA Tesla V100 GPU.The experimental result shows that the GPU implementation attains a speed-up factor of 318 and 16.19 over the sequential CPU implementation and the parallel multi-core CPU implementation with 160 threads, respectively. The second contribution of this paper is to propose an approximation method using machine learning with deep neural networks. After learning the network with the tile art images generated by the greedy approach as training dataset, it can generate tile art images that well-reproduce the original images with tile patterns. Moreover, we show an additional machine learning technique by repeating the forwarding computation for the generated tile art image as an input image. As a result, using this technique, we can generate a tile art images with clear shape of tiles.

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Section: Introductionmentioning

confidence: 99%

Tile art image generation using parallel greedy algorithm on the GPU and its approximation with machine learning

Matsumura

Tokura

Kuroda

et al. 2019

Concurrency and Computation

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show abstract

“…A recent survey over IBAR methods is provided in [1]. Nonetheless, designing new artistic styles remains a challenging research topic, since there are so many types of art in the real world, such as watercolor, oil, pen-andink, pencil drawing, and pointillism [2], as well as paper-cut, embroidery, and pyrography from China [3].…”

Section: Introductionmentioning

confidence: 99%

“…We generated various image data field using different image features, and then field coupling is implemented in order to create a sand painting filter. (2) How could the sand painting-like effects be automatically produced with a field coupling-based algorithm? We proposed a field coupling-based pipeline, which used an original image as input and produced sand painting-like effects.…”

Section: Introductionmentioning

confidence: 99%

Field Coupling-Based Image Filter for Sand Painting Stylization

Xia

2018

Mathematical Problems in Engineering

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Sand painting is a very new and popular performance art technique, and it has important meaning for the artistic creation. Computer-aided sand painting is now in the ascendant, whose fully automated mechanism is still an attractive challenge. Image data field, inspired from short-range nuclear force in physics, is introduced into sand painting stylization. With preserving edges and features, a fully automatic image filter pipeline based on image field coupling is proposed, which consists of three main steps, including image data field generating, multiscale field coupling, and additional details optimizing. The visual comparisons indicate that the proposed pipeline and image filter are feasible and effective, and sand painting-like artistic images can be produced by using multiscale field coupling. The qualities of various rendering images are also investigated from the perspective of feature similarity measures. The quantitative and qualitative results suggest that the field coupling-based filter is appropriate for sand painting stylization, and the time cost is satisfied for practice applications. Generally, the proposed method provides a reference for automatic creation of computer-aided sand painting art.

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