抄録
A low-poly image is a minimalist style of art that is currently widely used. It is an image derived from low-polygon 3D objects with an idea of image non-photorealistic abstraction. The trend of using low-poly images has accelerated rapidly since the introduction of vector images. Because low-poly images are based on vectors, the images are compact, scalable, editable, and easy to animate. Although semi-automatic low-poly image conversion tools exist, the resulting graphic generated from the tool does not resemble the original image in terms of its global structure. This paper presents an application that automatically creates a low-poly image that preserves global details, such as edges. Given a raster image, our algorithm automatically computes the polygons that best approximate the image. Our proposed algorithm is mainly based on K-means segmentation, contour extraction, the Ramer-Douglas-Peucker simplification, and the Delaunay triangulation. The output image is in a vector file format that can be easily further manipulated. For evaluation purposes, we distributed questionnaires to 30 participants that were comprised of 30 low-poly image sets; each set contained a low-poly image generated using our method and one generated using another method. From the experiment, we found that the majority of participants preferred the low-poly images generated using our method.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 131-139 |
| ページ数 | 9 |
| ジャーナル | Journal for Geometry and Graphics |
| 巻 | 21 |
| 発行部数 | 1 |
| 出版物ステータス | Published - 2017 1 1 |
| 外部発表 | Yes |
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ASJC Scopus subject areas
- Applied Psychology
- Geometry and Topology
- Applied Mathematics
これを引用
Low-poly image stylization. / Uasmith, Thitiwudh; Pukkaman, Tantikorn; Peeraya, Sripian.
：: Journal for Geometry and Graphics, 巻 21, 番号 1, 01.01.2017, p. 131-139.研究成果: Article
}
TY - JOUR
T1 - Low-poly image stylization
AU - Uasmith, Thitiwudh
AU - Pukkaman, Tantikorn
AU - Peeraya, Sripian
PY - 2017/1/1
Y1 - 2017/1/1
N2 - A low-poly image is a minimalist style of art that is currently widely used. It is an image derived from low-polygon 3D objects with an idea of image non-photorealistic abstraction. The trend of using low-poly images has accelerated rapidly since the introduction of vector images. Because low-poly images are based on vectors, the images are compact, scalable, editable, and easy to animate. Although semi-automatic low-poly image conversion tools exist, the resulting graphic generated from the tool does not resemble the original image in terms of its global structure. This paper presents an application that automatically creates a low-poly image that preserves global details, such as edges. Given a raster image, our algorithm automatically computes the polygons that best approximate the image. Our proposed algorithm is mainly based on K-means segmentation, contour extraction, the Ramer-Douglas-Peucker simplification, and the Delaunay triangulation. The output image is in a vector file format that can be easily further manipulated. For evaluation purposes, we distributed questionnaires to 30 participants that were comprised of 30 low-poly image sets; each set contained a low-poly image generated using our method and one generated using another method. From the experiment, we found that the majority of participants preferred the low-poly images generated using our method.
AB - A low-poly image is a minimalist style of art that is currently widely used. It is an image derived from low-polygon 3D objects with an idea of image non-photorealistic abstraction. The trend of using low-poly images has accelerated rapidly since the introduction of vector images. Because low-poly images are based on vectors, the images are compact, scalable, editable, and easy to animate. Although semi-automatic low-poly image conversion tools exist, the resulting graphic generated from the tool does not resemble the original image in terms of its global structure. This paper presents an application that automatically creates a low-poly image that preserves global details, such as edges. Given a raster image, our algorithm automatically computes the polygons that best approximate the image. Our proposed algorithm is mainly based on K-means segmentation, contour extraction, the Ramer-Douglas-Peucker simplification, and the Delaunay triangulation. The output image is in a vector file format that can be easily further manipulated. For evaluation purposes, we distributed questionnaires to 30 participants that were comprised of 30 low-poly image sets; each set contained a low-poly image generated using our method and one generated using another method. From the experiment, we found that the majority of participants preferred the low-poly images generated using our method.
KW - Image abstraction
KW - Image triangulation
KW - Image vectorization
KW - Low-poly image
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M3 - Article
AN - SCOPUS:85021837878
VL - 21
SP - 131
EP - 139
JO - Journal for Geometry and Graphics
JF - Journal for Geometry and Graphics
SN - 1433-8157
IS - 1
ER -