Band-Sifting Decomposition for Image-Based Material Editing
Photographers often "prep" their subjects to achieve various effects; for example, toning down overly shiny skin, covering blotches, etc. Making such adjustments digitally after a shoot is possible, but difficult without good tools and good skills. Making such adjustments to video footage...
| Main Authors: | , , , |
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| Format: | Article |
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Association for Computing Machinery (ACM)
2017
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| Online Access: | http://hdl.handle.net/1721.1/111978 https://orcid.org/0000-0003-2222-6775 |
| _version_ | 1811085251441590272 |
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| author | Boyadzhiev, Ivaylo Bala, Kavita Paris, Sylvain Adelson, Edward H |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Boyadzhiev, Ivaylo Bala, Kavita Paris, Sylvain Adelson, Edward H |
| author_sort | Boyadzhiev, Ivaylo |
| collection | MIT |
| description | Photographers often "prep" their subjects to achieve various effects; for example, toning down overly shiny skin, covering blotches, etc. Making such adjustments digitally after a shoot is possible, but difficult without good tools and good skills. Making such adjustments to video footage is harder still. We describe and study a set of 2D image operations, based on multiscale image analysis, that are easy and straightforward and that can consistently modify perceived material properties. These operators first build a subband decomposition of the image and then selectively modify the coefficients within the subbands. We call this selection process band sifting. We show that different siftings of the coefficients can be used to modify the appearance of properties such as gloss, smoothness, pigmentation, or weathering. The band-sifting operators have particularly striking effects when applied to faces; they can provide "knobs" to make a face look wetter or drier, younger or older, and with heavy or light variation in pigmentation. Through user studies, we identify a set of operators that yield consistent subjective effects for a variety of materials and scenes. We demonstrate that these operators are also useful for processing video sequences. |
| first_indexed | 2024-09-23T13:05:59Z |
| format | Article |
| id | mit-1721.1/111978 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T13:05:59Z |
| publishDate | 2017 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/1119782022-10-01T13:03:40Z Band-Sifting Decomposition for Image-Based Material Editing Boyadzhiev, Ivaylo Bala, Kavita Paris, Sylvain Adelson, Edward H Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Adelson, Edward H Photographers often "prep" their subjects to achieve various effects; for example, toning down overly shiny skin, covering blotches, etc. Making such adjustments digitally after a shoot is possible, but difficult without good tools and good skills. Making such adjustments to video footage is harder still. We describe and study a set of 2D image operations, based on multiscale image analysis, that are easy and straightforward and that can consistently modify perceived material properties. These operators first build a subband decomposition of the image and then selectively modify the coefficients within the subbands. We call this selection process band sifting. We show that different siftings of the coefficients can be used to modify the appearance of properties such as gloss, smoothness, pigmentation, or weathering. The band-sifting operators have particularly striking effects when applied to faces; they can provide "knobs" to make a face look wetter or drier, younger or older, and with heavy or light variation in pigmentation. Through user studies, we identify a set of operators that yield consistent subjective effects for a variety of materials and scenes. We demonstrate that these operators are also useful for processing video sequences. 2017-10-26T19:58:15Z 2017-10-26T19:58:15Z 2015-10 2015-06 2017-10-25T17:38:29Z Article http://purl.org/eprint/type/JournalArticle 0730-0301 http://hdl.handle.net/1721.1/111978 Boyadzhiev, Ivaylo et al. “Band-Sifting Decomposition for Image-Based Material Editing.” ACM Transactions on Graphics 34, 5 (November 2015): 1–16 © 2015 The Author(s) https://orcid.org/0000-0003-2222-6775 http://dx.doi.org/10.1145/2809796 ACM Transactions on Graphics Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for Computing Machinery (ACM) Other univ. web domain |
| spellingShingle | Boyadzhiev, Ivaylo Bala, Kavita Paris, Sylvain Adelson, Edward H Band-Sifting Decomposition for Image-Based Material Editing |
| title | Band-Sifting Decomposition for Image-Based Material Editing |
| title_full | Band-Sifting Decomposition for Image-Based Material Editing |
| title_fullStr | Band-Sifting Decomposition for Image-Based Material Editing |
| title_full_unstemmed | Band-Sifting Decomposition for Image-Based Material Editing |
| title_short | Band-Sifting Decomposition for Image-Based Material Editing |
| title_sort | band sifting decomposition for image based material editing |
| url | http://hdl.handle.net/1721.1/111978 https://orcid.org/0000-0003-2222-6775 |
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