Face painting: querying art with photos
We study the problem of matching photos of a person to paintings of that person, in order to retrieve similar paintings given a query photo. This is challenging as paintings span many media (oil, ink, watercolor) and can vary tremendously in style (caricature, pop art, minimalist). We make the follo...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
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British Machine Vision Association
2015
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| _version_ | 1826315168223592448 |
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| author | Crowley, EJ Parkhi, OM Zisserman, A |
| author_facet | Crowley, EJ Parkhi, OM Zisserman, A |
| author_sort | Crowley, EJ |
| collection | OXFORD |
| description | We study the problem of matching photos of a person to paintings of that person, in order to retrieve similar paintings given a query photo. This is challenging as paintings span many media (oil, ink, watercolor) and can vary tremendously in style (caricature, pop art, minimalist). We make the following contributions: (i) we show that, depending on the face representation used, performance can be improved substantially by learning -- either by a linear projection matrix common across identities, or by a per-identity classifier. We compare Fisher Vector and Convolutional Neural Network representations for this task; (ii) we introduce new datasets for learning and evaluating this problem; (iii) we also consider the reverse problem of retrieving photos from a large corpus given a painting; and finally, (iv) using the learnt descriptors, we show that, given a photo of a person, we are able to find their doppelgänger in a large dataset of oil paintings, and how this result can be varied by modifying attributes (e.g. frowning, old looking). |
| first_indexed | 2024-12-09T03:20:45Z |
| format | Conference item |
| id | oxford-uuid:c9f058a7-a2d8-4edd-b351-91ea81f4e582 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-12-09T03:20:45Z |
| publishDate | 2015 |
| publisher | British Machine Vision Association |
| record_format | dspace |
| spelling | oxford-uuid:c9f058a7-a2d8-4edd-b351-91ea81f4e5822024-11-05T14:32:42ZFace painting: querying art with photosConference itemhttp://purl.org/coar/resource_type/c_5794uuid:c9f058a7-a2d8-4edd-b351-91ea81f4e582EnglishSymplectic ElementsBritish Machine Vision Association2015Crowley, EJParkhi, OMZisserman, AWe study the problem of matching photos of a person to paintings of that person, in order to retrieve similar paintings given a query photo. This is challenging as paintings span many media (oil, ink, watercolor) and can vary tremendously in style (caricature, pop art, minimalist). We make the following contributions: (i) we show that, depending on the face representation used, performance can be improved substantially by learning -- either by a linear projection matrix common across identities, or by a per-identity classifier. We compare Fisher Vector and Convolutional Neural Network representations for this task; (ii) we introduce new datasets for learning and evaluating this problem; (iii) we also consider the reverse problem of retrieving photos from a large corpus given a painting; and finally, (iv) using the learnt descriptors, we show that, given a photo of a person, we are able to find their doppelgänger in a large dataset of oil paintings, and how this result can be varied by modifying attributes (e.g. frowning, old looking). |
| spellingShingle | Crowley, EJ Parkhi, OM Zisserman, A Face painting: querying art with photos |
| title | Face painting: querying art with photos |
| title_full | Face painting: querying art with photos |
| title_fullStr | Face painting: querying art with photos |
| title_full_unstemmed | Face painting: querying art with photos |
| title_short | Face painting: querying art with photos |
| title_sort | face painting querying art with photos |
| work_keys_str_mv | AT crowleyej facepaintingqueryingartwithphotos AT parkhiom facepaintingqueryingartwithphotos AT zissermana facepaintingqueryingartwithphotos |