Hochang Lee, Sanghyun Seo, Seung-Tack Ryoo, K. Yoon
{"title":"定向纹理转移","authors":"Hochang Lee, Sanghyun Seo, Seung-Tack Ryoo, K. Yoon","doi":"10.1145/1809939.1809945","DOIUrl":null,"url":null,"abstract":"A texture transfer algorithm modifies the target image replacing the high frequency information with the example source image. Previous texture transfer techniques normally use such factors as color distance and standard deviation for selecting the best texture from the candidate sets. These factors are useful for expressing a texture effect of the example source in the target image, but are less than optimal for considering the object shape of the target image.\n In this paper, we propose a novel texture transfer algorithm to express the directional effect based on the flow of the target image. For this, we use a directional factor that considers the gradient direction of the target image. We add an additional energy term that respects the image gradient to the previous fast texture transfer algorithm. Additionally, we propose a method for estimating the directional factor weight value from the target image. We have tested our algorithm with various target images. Our algorithm can express a result image with the feature of the example source texture and the flow of the target image.","PeriodicalId":204343,"journal":{"name":"International Symposium on Non-Photorealistic Animation and Rendering","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"88","resultStr":"{\"title\":\"Directional texture transfer\",\"authors\":\"Hochang Lee, Sanghyun Seo, Seung-Tack Ryoo, K. Yoon\",\"doi\":\"10.1145/1809939.1809945\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A texture transfer algorithm modifies the target image replacing the high frequency information with the example source image. Previous texture transfer techniques normally use such factors as color distance and standard deviation for selecting the best texture from the candidate sets. These factors are useful for expressing a texture effect of the example source in the target image, but are less than optimal for considering the object shape of the target image.\\n In this paper, we propose a novel texture transfer algorithm to express the directional effect based on the flow of the target image. For this, we use a directional factor that considers the gradient direction of the target image. We add an additional energy term that respects the image gradient to the previous fast texture transfer algorithm. Additionally, we propose a method for estimating the directional factor weight value from the target image. We have tested our algorithm with various target images. Our algorithm can express a result image with the feature of the example source texture and the flow of the target image.\",\"PeriodicalId\":204343,\"journal\":{\"name\":\"International Symposium on Non-Photorealistic Animation and Rendering\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"88\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Non-Photorealistic Animation and Rendering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1809939.1809945\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Non-Photorealistic Animation and Rendering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1809939.1809945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A texture transfer algorithm modifies the target image replacing the high frequency information with the example source image. Previous texture transfer techniques normally use such factors as color distance and standard deviation for selecting the best texture from the candidate sets. These factors are useful for expressing a texture effect of the example source in the target image, but are less than optimal for considering the object shape of the target image.
In this paper, we propose a novel texture transfer algorithm to express the directional effect based on the flow of the target image. For this, we use a directional factor that considers the gradient direction of the target image. We add an additional energy term that respects the image gradient to the previous fast texture transfer algorithm. Additionally, we propose a method for estimating the directional factor weight value from the target image. We have tested our algorithm with various target images. Our algorithm can express a result image with the feature of the example source texture and the flow of the target image.