DocumentCode :
3428588
Title :
Modifying the Memorability of Face Photographs
Author :
Khosla, Aditya ; Bainbridge, Wilma A. ; Torralba, Antonio ; Oliva, Alfonso
Author_Institution :
Comput. Sci. & Artificial Intell. Lab., Massachusetts Inst. of Technol., Cambridge, MA, USA
fYear :
2013
fDate :
1-8 Dec. 2013
Firstpage :
3200
Lastpage :
3207
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.
Keywords :
computer vision; face recognition; photography; computer graphics; computer vision; crowd-sourcing experiment; face photograph; facial traits; human memory; memorability modification; mnemonic aids; nontrivial constraint; photo editing application; social networks; Computer vision; Cost function; Face; Measurement; Principal component analysis; Shape; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision (ICCV), 2013 IEEE International Conference on
Conference_Location :
Sydney, NSW
ISSN :
1550-5499
Type :
conf
DOI :
10.1109/ICCV.2013.397
Filename :
6751509
Link To Document :
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