Lesley Istead , Joe Istead , Andreea Pocol , Craig S. Kaplan
{"title":"A simple, stroke-based method for gesture drawing","authors":"Lesley Istead , Joe Istead , Andreea Pocol , Craig S. Kaplan","doi":"10.1016/j.vrih.2022.08.004","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Gesture drawing is a type of fluid, fast sketch with loose and roughly drawn lines that captures the motion and feeling of a subject. Although style transfer methods, which are able to learn a style from an input image and apply it to a secondary image, can reproduce many styles, they are currently unable to produce the flowing strokes of gesture drawings.</p></div><div><h3>Method</h3><p>In this paper, we present a method for producing gesture drawings that roughly depict objects or scenes with loose dancing contours and frantic textures. By following a gradient field, our method adapts stroke-based painterly rendering algorithms to produce long curved strokes. A rough, overdrawn appearance is created through a progressive refinement. In addition, we produce rough hatch strokes by altering the stroke direction. These add optional shading to gesture drawings.</p></div><div><h3>Results</h3><p>A wealth of parameters provide users the ability to adjust the output style, from short and rapid strokes to long and fluid strokes, and from swirling to straight lines. Potential stylistic outputs include pen-and-ink and colored pencil. We present several generated gesture drawings and discuss the application of our method to video.</p></div><div><h3>Conclusion</h3><p>Our stroke-based rendering algorithm produces convincing gesture drawings with numerous controllable parameters, permitting the creation of a variety of styles.</p></div>","PeriodicalId":33538,"journal":{"name":"Virtual Reality Intelligent Hardware","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096579622000791/pdf?md5=5d6ede6955247fdfc333f73a0cddaa0d&pid=1-s2.0-S2096579622000791-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Virtual Reality Intelligent Hardware","FirstCategoryId":"1093","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096579622000791","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Gesture drawing is a type of fluid, fast sketch with loose and roughly drawn lines that captures the motion and feeling of a subject. Although style transfer methods, which are able to learn a style from an input image and apply it to a secondary image, can reproduce many styles, they are currently unable to produce the flowing strokes of gesture drawings.
Method
In this paper, we present a method for producing gesture drawings that roughly depict objects or scenes with loose dancing contours and frantic textures. By following a gradient field, our method adapts stroke-based painterly rendering algorithms to produce long curved strokes. A rough, overdrawn appearance is created through a progressive refinement. In addition, we produce rough hatch strokes by altering the stroke direction. These add optional shading to gesture drawings.
Results
A wealth of parameters provide users the ability to adjust the output style, from short and rapid strokes to long and fluid strokes, and from swirling to straight lines. Potential stylistic outputs include pen-and-ink and colored pencil. We present several generated gesture drawings and discuss the application of our method to video.
Conclusion
Our stroke-based rendering algorithm produces convincing gesture drawings with numerous controllable parameters, permitting the creation of a variety of styles.