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research-article

What Makes a Photograph Memorable?

Published: 01 July 2014 Publication History

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.

Cited By

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  • (2024)Reconciling the Rift Between Recognition and Recall: Insights from a Video Memorability Drawing ExperimentProceedings of the 2024 International Conference on Multimedia Retrieval10.1145/3652583.3657584(1190-1198)Online publication date: 30-May-2024
  • (2024)VMemNet: A Deep Collaborative Spatial-Temporal Network With Attention Representation for Video Memorability PredictionIEEE Transactions on Multimedia10.1109/TMM.2023.332786126(4926-4937)Online publication date: 1-Jan-2024
  • (2023)Stacked Bin Convolutional Neural Networks based Sparse Low-Rank Regressor: Robust, Scalable and Novel Model for Memorability Prediction of VideosMultimedia Tools and Applications10.1007/s11042-023-15128-z82:26(40799-40817)Online publication date: 1-Apr-2023
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Information & Contributors

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Published In

cover image IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence  Volume 36, Issue 7
July 2014
205 pages

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IEEE Computer Society

United States

Publication History

Published: 01 July 2014

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Cited By

View all
  • (2024)Reconciling the Rift Between Recognition and Recall: Insights from a Video Memorability Drawing ExperimentProceedings of the 2024 International Conference on Multimedia Retrieval10.1145/3652583.3657584(1190-1198)Online publication date: 30-May-2024
  • (2024)VMemNet: A Deep Collaborative Spatial-Temporal Network With Attention Representation for Video Memorability PredictionIEEE Transactions on Multimedia10.1109/TMM.2023.332786126(4926-4937)Online publication date: 1-Jan-2024
  • (2023)Stacked Bin Convolutional Neural Networks based Sparse Low-Rank Regressor: Robust, Scalable and Novel Model for Memorability Prediction of VideosMultimedia Tools and Applications10.1007/s11042-023-15128-z82:26(40799-40817)Online publication date: 1-Apr-2023
  • (2023)The Impact of Importance-Aware Dataset Partitioning on Data-Parallel Training of Deep Neural NetworksDistributed Applications and Interoperable Systems10.1007/978-3-031-35260-7_5(74-89)Online publication date: 19-Jun-2023
  • (2022)Affective Video Tagging Framework using Human Attention Modelling through EEG SignalsInternational Journal of Intelligent Information Technologies10.4018/IJIIT.30696818:1(1-18)Online publication date: 4-Aug-2022
  • (2022)Human Latent Metrics: Perceptual and Cognitive Response Correlates to Distance in GAN Latent Space for Facial ImagesACM Symposium on Applied Perception 202210.1145/3548814.3551460(1-10)Online publication date: 22-Sep-2022
  • (2022)VisRecall: Quantifying Information Visualisation Recallability via Question AnsweringIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.319816328:12(4995-5005)Online publication date: 1-Dec-2022
  • (2022)High level visual scene classification using background knowledge of objectsMultimedia Tools and Applications10.1007/s11042-021-11701-681:3(3663-3692)Online publication date: 1-Jan-2022
  • (2022)When Deep Classifiers Agree: Analyzing Correlations Between Learning Order and Image StatisticsComputer Vision – ECCV 202210.1007/978-3-031-20074-8_23(397-413)Online publication date: 23-Oct-2022
  • (2022)Imageability-Based Multi-modal Analysis of Urban Environments for Architects and ArtistsImage Analysis and Processing. ICIAP 2022 Workshops10.1007/978-3-031-13321-3_18(198-209)Online publication date: 23-May-2022
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