Display options
Cite
Aharonson V, Babshet K, Korczyn A. Towards a computerized estimation of visual complexity in images: Data to assess the association of computed visual complexity features to human responses in visual tasks. Data Brief. 2020;32:106108doi: 10.1016/j.dib.2020.106108.
Aharonson, V., Babshet, K., & Korczyn, A. (2020). Towards a computerized estimation of visual complexity in images: Data to assess the association of computed visual complexity features to human responses in visual tasks. Data in brief, 32106108. https://doi.org/10.1016/j.dib.2020.106108
Aharonson, Vered, et al. "Towards a computerized estimation of visual complexity in images: Data to assess the association of computed visual complexity features to human responses in visual tasks." Data in brief vol. 32 (2020): 106108. doi: https://doi.org/10.1016/j.dib.2020.106108
Aharonson V, Babshet K, Korczyn A. Towards a computerized estimation of visual complexity in images: Data to assess the association of computed visual complexity features to human responses in visual tasks. Data Brief. 2020 Aug 02;32:106108. doi: 10.1016/j.dib.2020.106108. eCollection 2020 Oct. PMID: 32885004; PMCID: PMC7451812.
Copy Download .nbib Format: NLM
Share it on

Data Brief. 2020 Aug 02;32:106108. doi: 10.1016/j.dib.2020.106108. eCollection 2020 Oct.

Towards a computerized estimation of visual complexity in images: Data to assess the association of computed visual complexity features to human responses in visual tasks.

Data in brief

Vered Aharonson, Kanaka Babshet, Amos Korczyn

Affiliations

  1. School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa.
  2. Sackler School of Medicine, Tel Aviv University, Israel.

PMID: 32885004 PMCID: PMC7451812 DOI: 10.1016/j.dib.2020.106108

Abstract

Artificial vision has been extensively studied in the mathematical and computational Sciences. Concurrently, psychological studies attempt to describe visual cognition and the complexity of visual tasks as perceived by humans. The methods and the definitions of vision used by these two disciplines are disjointed. Particularly, an explanation of computer vision performance by human-perceived attributes, if attempted, can only be inferred. This article describes a dataset collected to explore the association between computer-extracted visual attributes and human-perceived attributes in the context of cognitive tasks. The data was acquired from a cohort of 406 subjects, ages 40-90, in the presence of a healthcare professional who assessed that the subjects had no cognitive or motor disorder. The subjects performed computerized cognitive tests which entailed tasks of recognition or recall of an image in a set of three images, presented on the computer screen. The images were simple black and white abstract square shapes. The latencies of the subjects' responses, by keyboard key press, to each task were logged. The data contains 3 parts: the images presented in each task, described by binary vectors for black and white coding, a response time logged for each task and the subjects' age, gender, and computer proficiency. A preliminary comparison of computationally-extracted complexity features and subjects' performance is provided in the article entitled "Linking computerized and perceived attributes of visual complexity" [1].

© 2020 The Authors.

Keywords: Black and white image stimuli; Cognitive tests; Computational attributes; Image feature extraction; Visual complexity; Visual recall; Visual recognition

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article.

References

  1. Conscious Cogn. 2005 Jun;14(2):390-425 - PubMed
  2. Trends Cogn Sci. 2013 Mar;17(3):134-41 - PubMed
  3. Curr Alzheimer Res. 2007 Sep;4(4):364-9 - PubMed
  4. Comput Methods Programs Biomed. 2004 Jan;73(1):43-53 - PubMed
  5. Alzheimers Dement. 2007 Jan;3(1):23-7 - PubMed

Publication Types