Review of Image Memorability Prediction

Jie Liu, Dou-Dou Wang, Yan Wang, Hao Zhang
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引用次数: 1

Abstract

With the development of information technology and networks, images can be seen everywhere in life. When people browse magazines and the Internet, they come into contact with thousands of images, some of which remain in people's memories, while others are forgotten. Isola et al. first proposed the concept of image memorability and proved that image memorability is an intrinsic and stable attribute of images and can be shared among different viewers. Image memorability prediction has important research value and can be applied to education, advertising and other fields. In order to promote the research of image memorability prediction, the main theories and methods are summarized. Based on the comparison and analysis of the literatures related to image memorability prediction, this paper firstly reviews the proposal and quantification of the concept of image memorability. The features that affect the image memorability and the methods for extracting features are analyzed. The prediction of predictive image memorability is introduced in detail. The prediction is constructed based on Support Vector Machine and Convolution Neural Network and using different features that affect image memorability. Finally, the future work of image memorability is summarized and forecasted.
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图像记忆预测研究综述
随着信息技术和网络的发展,图像在生活中随处可见。当人们浏览杂志和互联网时,他们接触到成千上万的图像,其中一些留在人们的记忆中,而另一些则被遗忘了。Isola等人首先提出了图像可记忆性的概念,并证明图像可记忆性是图像固有的、稳定的属性,可以在不同的观看者之间共享。图像记忆预测具有重要的研究价值,可应用于教育、广告等领域。为了促进图像记忆预测的研究,总结了目前图像记忆预测的主要理论和方法。在对图像可记忆性预测相关文献进行比较分析的基础上,本文首先回顾了图像可记忆性概念的提出和定量化。分析了影响图像记忆的特征及其提取方法。详细介绍了预测图像记忆性的预测方法。该预测基于支持向量机和卷积神经网络,并利用影响图像记忆的不同特征。最后,对图像记忆今后的工作进行了总结和展望。
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