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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Khosla, A. Bainbridge, W.A. Torralba, A. Oliva, A. |
| Copyright Year | 2013 |
| Description | Author affiliation: Comput. Sci. & Artificial Intell. Lab., Massachusetts Inst. of Technol., Cambridge, MA, USA (Khosla, A.; Bainbridge, W.A.; Torralba, A.; Oliva, A.) |
| Abstract | Contemporary life bombards us with many new images of faces every day, which poses non-trivial constraints on human memory. The vast majority of face photographs are intended to be remembered, either because of personal relevance, commercial interests or because the pictures were deliberately designed to be memorable. Can we make a portrait more memorable or more forgettable automatically? Here, we provide a method to modify the memorability of individual face photographs, while keeping the identity and other facial traits (e.g. age, attractiveness, and emotional magnitude) of the individual fixed. We show that face photographs manipulated to be more memorable (or more forgettable) are indeed more often remembered (or forgotten) in a crowd-sourcing experiment with an accuracy of 74%. Quantifying and modifying the 'memorability' of a face lends itself to many useful applications in computer vision and graphics, such as mnemonic aids for learning, photo editing applications for social networks and tools for designing memorable advertisements. |
| Sponsorship | IEEE Comput. Soc. |
| Starting Page | 3200 |
| Ending Page | 3207 |
| File Size | 2847776 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781479928408 |
| ISSN | 15505499 |
| DOI | 10.1109/ICCV.2013.397 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-12-01 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Face Shape Measurement Support vector machines Principal component analysis Cost function Computer vision |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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