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[求助]
非常感谢，麻烦帮我查下这篇论文SCIE检索了吗?
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标题：A Mean-Shift-Based Feature Descriptor for Wide Baseline Stereo Matching 期刊：Mathematical Problems in Engineering 作者：Dou, Yiwen; Hao, Kuangrong; Ding, Yongsheng; Mao, Min 其他：2015(7):1-14. DOI: 10.1155/2015/398756 |
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木头虫925: 金币+15, ★★★★★最佳答案, 检索的如此详细，非常感谢！ 2016-05-11 09:46:05
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感谢参与，应助指数 +1
木头虫925: 金币+15, ★★★★★最佳答案, 检索的如此详细，非常感谢！ 2016-05-11 09:46:05
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lazy锦溪: LS-EPI+1, 感谢应助！ 2016-05-13 09:38:21
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A Mean-Shift-Based Feature Descriptor for Wide Baseline Stereo Matching 作者  ou, YW (Dou, Yiwen)[ 1 ] ; Hao, KR (Hao, Kuangrong)[ 1 ] ; Ding, YS (Ding, Yongsheng)[ 1 ] ; Mao, M (Mao, Min)[ 1 ] MATHEMATICAL PROBLEMS IN ENGINEERING 文献号: 398756 DOI: 10.1155/2015/398756 出版年: 2015 查看期刊信息 MATHEMATICAL PROBLEMS IN ENGINEERING 出版商 HINDAWI PUBLISHING CORP, 410 PARK AVENUE, 15TH FLOOR, #287 PMB, NEW YORK, NY 10022 USA ISSN: 1024-123X eISSN: 1563-5147 研究领域 Engineering Mathematics 摘要 We propose a novel Mean-Shift-based building approach in wide baseline. Initially, scale-invariance feature transform (SIFT) approach is used to extract relatively stable feature points. As to each matching SIFT feature point, it needs a reasonable neighborhood range so as to choose feature points set. Subsequently, in view of selecting repeatable and high robust feature points, Mean-Shift controls corresponding feature scale. At last, our approach is employed to depth image acquirement in wide baseline and Graph Cut algorithm optimizes disparity information. Compared with the existing methods such as SIFT, speeded up robust feature (SURF), and normalized cross-correlation (NCC), the presented approach has the advantages of higher robustness and accuracy rate. Experimental results on low resolution image and weak feature description in wide baseline confirm the validity of our approach. 关键词 KeyWords Plus:IMAGE; SIFT; REGIONS; SEGMENTATION; CONVERGENCE; ALGORITHM; TRACKING 作者信息 通讯作者地址: Hao, KR (通讯作者) Donghua Univ, Engn Res Ctr Digitized Text & Apparel Technol, Minist Educ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China. 增强组织信息的名称 Donghua University 地址: [ 1 ] Donghua Univ, Engn Res Ctr Digitized Text & Apparel Technol, Minist Educ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China 增强组织信息的名称 Donghua University 电子邮件地址:krhao@dhu.edu.cn 基金资助致谢 基金资助机构 授权号 Key Project of the National Nature Science Foundation of China 61134009 National Nature Science Foundation of China 61473077 61473078 Program for Changjiang Scholars from the Ministry of Education Specialized Research Fund for Shanghai Leading Talents Project of the Shanghai Committee of Science and Technology 13JC1407500 Innovation Program of Shanghai Municipal Education Commission 14ZZ067 查看基金资助信息关闭基金资助信息 This work was supported in part by the Key Project of the National Nature Science Foundation of China (no. 61134009), the National Nature Science Foundation of China (nos. 61473077 and 61473078), Program for Changjiang Scholars from the Ministry of Education, Specialized Research Fund for Shanghai Leading Talents, Project of the Shanghai Committee of Science and Technology (no. 13JC1407500), and Innovation Program of Shanghai Municipal Education Commission (no. 14ZZ067). 出版商 HINDAWI PUBLISHING CORP, 410 PARK AVENUE, 15TH FLOOR, #287 PMB, NEW YORK, NY 10022 USA 类别 / 分类 研究方向:Engineering; Mathematics Web of Science 类别:Engineering, Multidisciplinary; Mathematics, Interdisciplinary Applications 文献信息 文献类型:Article 语种:English 入藏号: WOS:000366423100001 ISSN: 1024-123X eISSN: 1563-5147 其他信息 IDS 号: CY5BO Web of Science 核心合集中的 "引用的参考文献": 30 Web of Science 核心合集中的 "被引频次": 0 影响因子 0.762 0.798 2014 5 年 JCR® 类别 类别中的排序 JCR 分区 ENGINEERING, MULTIDISCIPLINARY 54/85 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS 70/99 Q3 数据来自第 2014 版 Journal Citation Reports® |
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