Scale and Object Aware Image Thumbnailing.
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| Title: | Scale and Object Aware Image Thumbnailing. |
|---|---|
| Authors: | Sun, Jin1 jinsun@cs.umd.edu, Ling, Haibin1 hbling@temple.edu |
| Source: | International Journal of Computer Vision. Sep2013, Vol. 104 Issue 2, p135-153. 19p. 12 Color Photographs, 2 Diagrams, 4 Charts, 3 Graphs. |
| Subjects: | Thumbnail images (Image processing), Algorithms, Qualitative research, Digital image processing, Image reconstruction, Visual acuity, Contrast sensitivity (Vision) |
| Abstract: | In this paper we study effective approaches to create thumbnails from input images. Since a thumbnail will eventually be presented to and perceived by a human visual system, a thumbnailing algorithm should consider several important issues in the process including thumbnail scale, object completeness and local structure smoothness. To address these issues, we propose a new thumbnailing framework named scale and object aware thumbnailing (SOAT), which contains two components focusing respectively on saliency measure and thumbnail warping/cropping. The first component, named scale and object aware saliency (SOAS), models the human perception of thumbnails using visual acuity theory, which takes thumbnail scale into consideration. In addition, the 'objectness' measurement (Alexe et al. ) is integrated in SOAS, as to preserve object completeness. The second component uses SOAS to guide the thumbnailing based on either retargeting or cropping. The retargeting version uses the thin-plate-spline (TPS) warping for preserving structure smoothness. An extended seam carving algorithm is developed to sample control points used for TPS model estimation. The cropping version searches a cropping window that balances the spatial efficiency and SOAS-based content preservation. The proposed algorithms were evaluated in three experiments: a quantitative user study to evaluate thumbnail browsing efficiency, a quantitative user study for subject preference, and a qualitative study on the RetargetMe dataset. In all studies, SOAT demonstrated promising performances in comparison with state-of-the-art algorithms. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Computer Vision is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 89397632 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Scale and Object Aware Image Thumbnailing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sun%2C+Jin%22">Sun, Jin</searchLink><relatesTo>1</relatesTo><i> jinsun@cs.umd.edu</i><br /><searchLink fieldCode="AR" term="%22Ling%2C+Haibin%22">Ling, Haibin</searchLink><relatesTo>1</relatesTo><i> hbling@temple.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Computer+Vision%22">International Journal of Computer Vision</searchLink>. Sep2013, Vol. 104 Issue 2, p135-153. 19p. 12 Color Photographs, 2 Diagrams, 4 Charts, 3 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Thumbnail+images+%28Image+processing%29%22">Thumbnail images (Image processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Qualitative+research%22">Qualitative research</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+image+processing%22">Digital image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Image+reconstruction%22">Image reconstruction</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+acuity%22">Visual acuity</searchLink><br /><searchLink fieldCode="DE" term="%22Contrast+sensitivity+%28Vision%29%22">Contrast sensitivity (Vision)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this paper we study effective approaches to create thumbnails from input images. Since a thumbnail will eventually be presented to and perceived by a human visual system, a thumbnailing algorithm should consider several important issues in the process including thumbnail scale, object completeness and local structure smoothness. To address these issues, we propose a new thumbnailing framework named scale and object aware thumbnailing (SOAT), which contains two components focusing respectively on saliency measure and thumbnail warping/cropping. The first component, named scale and object aware saliency (SOAS), models the human perception of thumbnails using visual acuity theory, which takes thumbnail scale into consideration. In addition, the 'objectness' measurement (Alexe et al. ) is integrated in SOAS, as to preserve object completeness. The second component uses SOAS to guide the thumbnailing based on either retargeting or cropping. The retargeting version uses the thin-plate-spline (TPS) warping for preserving structure smoothness. An extended seam carving algorithm is developed to sample control points used for TPS model estimation. The cropping version searches a cropping window that balances the spatial efficiency and SOAS-based content preservation. The proposed algorithms were evaluated in three experiments: a quantitative user study to evaluate thumbnail browsing efficiency, a quantitative user study for subject preference, and a qualitative study on the RetargetMe dataset. In all studies, SOAT demonstrated promising performances in comparison with state-of-the-art algorithms. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Computer Vision is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11263-013-0618-z Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 135 Subjects: – SubjectFull: Thumbnail images (Image processing) Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Qualitative research Type: general – SubjectFull: Digital image processing Type: general – SubjectFull: Image reconstruction Type: general – SubjectFull: Visual acuity Type: general – SubjectFull: Contrast sensitivity (Vision) Type: general Titles: – TitleFull: Scale and Object Aware Image Thumbnailing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sun, Jin – PersonEntity: Name: NameFull: Ling, Haibin IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2013 Type: published Y: 2013 Identifiers: – Type: issn-print Value: 09205691 Numbering: – Type: volume Value: 104 – Type: issue Value: 2 Titles: – TitleFull: International Journal of Computer Vision Type: main |
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