research-article

Toward Quantifying Ambiguities in Artistic Images

Authors:

Zoya Bylinskii,

Aaron Hertzmann, and

Robert PepperellAuthors Info & Claims

ACM Transactions on Applied Perception (TAP), Volume 17, Issue 4

Article No.: 13, Pages 1 - 10

https://doi.org/10.1145/3418054

Published: 06 November 2020 Publication History

Abstract

It has long been hypothesized that perceptual ambiguities play an important role in aesthetic experience: A work with some ambiguity engages a viewer more than one that does not. However, current frameworks for testing this theory are limited by the availability of stimuli and data collection methods. This article presents an approach to measuring the perceptual ambiguity of a collection of images. Crowdworkers are asked to describe image content, after different viewing durations. Experiments are performed using images created with Generative Adversarial Networks, using the Artbreeder website. We show that text processing of viewer responses can provide a fine-grained way to measure and describe image ambiguities.

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Cited By

Pepperell R(2023)Being alive to the world: an artist's perspective on predictive processingPhilosophical Transactions of the Royal Society B: Biological Sciences10.1098/rstb.2022.0429379:1895Online publication date: 18-Dec-2023
https://doi.org/10.1098/rstb.2022.0429
Frascaroli JLeder HBrattico EVan de Cruys S(2023)Aesthetics and predictive processing: grounds and prospects of a fruitful encounterPhilosophical Transactions of the Royal Society B: Biological Sciences10.1098/rstb.2022.0410379:1895Online publication date: 18-Dec-2023
https://doi.org/10.1098/rstb.2022.0410
Goetschalckx LAndonian AWagemans J(2021)Generative adversarial networks unlock new methods for cognitive scienceTrends in Cognitive Sciences10.1016/j.tics.2021.06.00625:9(788-801)Online publication date: Sep-2021
https://doi.org/10.1016/j.tics.2021.06.006

Index Terms

Toward Quantifying Ambiguities in Artistic Images
1. Applied computing
  1. Arts and humanities

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Published In

cover image ACM Transactions on Applied Perception

ACM Transactions on Applied Perception Volume 17, Issue 4

Special Issue on SAP 2020

October 2020

65 pages

ISSN:1544-3558

EISSN:1544-3965

DOI:10.1145/3434049

Editors:
Martin Giese
University of Tübingen, Germany
,
Victoria Interrante
University of Minnesota, USA

Issue’s Table of Contents

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2020

Accepted: 01 August 2020

Received: 01 June 2020

Published in TAP Volume 17, Issue 4

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Cited By

Pepperell R(2023)Being alive to the world: an artist's perspective on predictive processingPhilosophical Transactions of the Royal Society B: Biological Sciences10.1098/rstb.2022.0429379:1895Online publication date: 18-Dec-2023
https://doi.org/10.1098/rstb.2022.0429
Frascaroli JLeder HBrattico EVan de Cruys S(2023)Aesthetics and predictive processing: grounds and prospects of a fruitful encounterPhilosophical Transactions of the Royal Society B: Biological Sciences10.1098/rstb.2022.0410379:1895Online publication date: 18-Dec-2023
https://doi.org/10.1098/rstb.2022.0410
Goetschalckx LAndonian AWagemans J(2021)Generative adversarial networks unlock new methods for cognitive scienceTrends in Cognitive Sciences10.1016/j.tics.2021.06.00625:9(788-801)Online publication date: Sep-2021
https://doi.org/10.1016/j.tics.2021.06.006

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