Proposal for a Composition Recommend System for Sketches in Illustration

The composition has a strong influence on the overall of the work in the quality of arrangement and the impression. While the type of composition makes an impression, the beginners may struggle to place the human subject in the initial stage of sketches. Therefore, we propose a method for the improvements to the placement of the human object in an illustration at the initial sketch stage in this paper. We implemented a system to generate the output image in two basic compositions by using human objects in based on the object detection method by using the deep learning. We conduct quantitative experiments to show the effectiveness of our method.

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Publication Details

Journal
Transactions of Japan Society of Kansei Engineering
Published
2024-11-27
DOI
https://doi.org/10.5057/jjske.tjske-d-24-00022
Primary Topic
Art, Technology, and Culture
Type
article
Field-Weighted Citation Impact
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article

Proposal for a Composition Recommend System for Sketches in Illustration

Makiba Sakamoto, Takayuki Fujiwara, Yosuke MORISHITA
Transactions of Japan Society of Kansei Engineering
Art, Technology, and Culture
article

Proposal for a Composition Recommend System for Sketches in Illustration

Makiba Sakamoto, Takayuki Fujiwara, Yosuke MORISHITA
article en

Abstract

The composition has a strong influence on the overall of the work in the quality of arrangement and the impression. While the type of composition makes an impression, the beginners may struggle to place the human subject in the initial stage of sketches. Therefore, we propose a method for the improvements to the placement of the human object in an illustration at the initial sketch stage in this paper. We implemented a system to generate the output image in two basic compositions by using human objects in based on the object detection method by using the deep learning. We conduct quantitative experiments to show the effectiveness of our method.

Transactions of Japan Society of Kansei EngineeringVol. 24(1)
Hokkaido Information University (JP)
Openalex Percentile: Top 68%
Art, Technology, and Culture
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