Fast Image Correspondence with Global Structure Projection
This paper presents a method for correspondence. This technique works by two recognizing images with steps: reference keypoint flat objects based on global keypoint structure selection and structure projection. The using of global keypoint structure is an extension of an orderless bag-of-features im...
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Published in | Journal of computer science and technology Vol. 27; no. 6; pp. 1281 - 1288 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
Boston
Springer US
01.11.2012
Springer Nature B.V Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China%Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai 200237 China |
Subjects | |
Online Access | Get full text |
ISSN | 1000-9000 1860-4749 |
DOI | 10.1007/s11390-012-1304-2 |
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Summary: | This paper presents a method for correspondence. This technique works by two recognizing images with steps: reference keypoint flat objects based on global keypoint structure selection and structure projection. The using of global keypoint structure is an extension of an orderless bag-of-features image representation, which is utilized by the proposed matching technique for computation efficiency. Specifically, our proposed method excels in the dataset of images containing "flat objects" such as CD covers, books, newspaper. The efficiency and accuracy of our proposed method has been tested on a database of nature pictures with flat objects and other kind of objects. The result shows our method works well in both occasions. |
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Bibliography: | object recognition, image correspoadence, structure projection, flat object 11-2296/TP This paper presents a method for correspondence. This technique works by two recognizing images with steps: reference keypoint flat objects based on global keypoint structure selection and structure projection. The using of global keypoint structure is an extension of an orderless bag-of-features image representation, which is utilized by the proposed matching technique for computation efficiency. Specifically, our proposed method excels in the dataset of images containing "flat objects" such as CD covers, books, newspaper. The efficiency and accuracy of our proposed method has been tested on a database of nature pictures with flat objects and other kind of objects. The result shows our method works well in both occasions. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23 |
ISSN: | 1000-9000 1860-4749 |
DOI: | 10.1007/s11390-012-1304-2 |