The Computational Memorability of Iconic Images

:speech_balloon: Speaker: Lisa Saleh and Nanne van Noord

:classical_building: Affiliation: Multimedia Analytics Lab, University of Amsterdam

Title: The Computational Memorability of Iconic Images

Abstract: The perception of historic events is frequently shaped by specific images that have been ascribed an iconic status. These images are widely reproduced and recognised and can therefore be considered memorable. A question that arises given such images is whether the memorability of iconic images is intrinsic or whether it is shaped. In this work we analyse the memorability of iconic images by means of computational techniques that are specifically designed to measure the intrinsic memorability of images. To judge whether iconic images are inherently more memorable we establish two baselines based on datasets of diverse imagery and of newspaper imagery. Our findings show that iconic images are not more memorable than modern day newspaper imagery or when compared to a diverse set of everyday images. In fact, by and large many of the iconic images analysed score on the low end of the memorability spectrum. Additionally, we explore the variation in memorability of reproductions of iconic images and find that certain images have been edited resulting in higher memorability scores, but that the images by and large are reproduced with memorability close to the original.

:newspaper: Link to paper

:file_folder: