基于视觉中心移位的视觉显著性检测

Jinge Hu, Jiang Xiong, Yuming Feng, B. Onasanya
{"title":"基于视觉中心移位的视觉显著性检测","authors":"Jinge Hu, Jiang Xiong, Yuming Feng, B. Onasanya","doi":"10.1109/ICACI52617.2021.9435891","DOIUrl":null,"url":null,"abstract":"The saliency areas extracted by traditional visual saliency detection methods are not clear enough. This paper presents a visual saliency detection method based on visual center offset. On the basis of pre-segmentation of the image, the significant areas of the image are extracted by combining the color contrast, color distribution and location characteristics. Using visual center transfer to simulate the visual transfer process of human observation, the image is analyzed at multiple scales. The results indicate that this approach is efficient because ROC curve and Precision-Recall performed well.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visual saliency detection based on visual center shift\",\"authors\":\"Jinge Hu, Jiang Xiong, Yuming Feng, B. Onasanya\",\"doi\":\"10.1109/ICACI52617.2021.9435891\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The saliency areas extracted by traditional visual saliency detection methods are not clear enough. This paper presents a visual saliency detection method based on visual center offset. On the basis of pre-segmentation of the image, the significant areas of the image are extracted by combining the color contrast, color distribution and location characteristics. Using visual center transfer to simulate the visual transfer process of human observation, the image is analyzed at multiple scales. The results indicate that this approach is efficient because ROC curve and Precision-Recall performed well.\",\"PeriodicalId\":382483,\"journal\":{\"name\":\"2021 13th International Conference on Advanced Computational Intelligence (ICACI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 13th International Conference on Advanced Computational Intelligence (ICACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACI52617.2021.9435891\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACI52617.2021.9435891","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

传统的视觉显著性检测方法提取的显著区域不够清晰。提出了一种基于视觉中心偏移量的视觉显著性检测方法。在对图像进行预分割的基础上,结合颜色对比、颜色分布和位置特征提取图像的重要区域。利用视觉中心传递模拟人类观察的视觉传递过程,对图像进行多尺度分析。结果表明,该方法具有良好的ROC曲线和查准率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visual saliency detection based on visual center shift
The saliency areas extracted by traditional visual saliency detection methods are not clear enough. This paper presents a visual saliency detection method based on visual center offset. On the basis of pre-segmentation of the image, the significant areas of the image are extracted by combining the color contrast, color distribution and location characteristics. Using visual center transfer to simulate the visual transfer process of human observation, the image is analyzed at multiple scales. The results indicate that this approach is efficient because ROC curve and Precision-Recall performed well.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信