What Makes a Photograph Memorable?
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Torralba_What makes.pdf
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10.49 MB
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Author(s)
Isola, Phillip John
Xiao, Jianxiong
Parikh, Devi
Torralba, Antonio
Oliva, Aude
Date Issued
June 2014
Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Isola, Phillip, Jianxiong Xiao, Devi Parikh, Antonio Torralba, and Aude Oliva. “What Makes a Photograph Memorable?” IEEE Trans. Pattern Anal. Mach. Intell. 36, no. 7 (July 2014): 1469–1482.
Version
Author's final manuscript
Abstract
When glancing at a magazine, or browsing the Internet, we are continuously exposed to photographs. Despite this overflow of visual information, humans are extremely good at remembering thousands of pictures along with some of their visual details. But not all images are equal in memory. Some stick in our minds while others are quickly forgotten. In this paper, we focus on the problem of predicting how memorable an image will be. We show that memorability is an intrinsic and stable property of an image that is shared across different viewers, and remains stable across delays. We introduce a database for which we have measured the probability that each picture will be recognized after a single view. We analyze a collection of image features, labels, and attributes that contribute to making an image memorable, and we train a predictor based on global image descriptors. We find that predicting image memorability is a task that can be addressed with current computer vision techniques. While making memorable images is a challenging task in visualization, photography, and education, this work is a first attempt to quantify this useful property of images.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/TPAMI.2013.200
