Single anchor sorting of visual appearance as an oriented graph

N. Moroney, I. Tastl, M. Gottwals, M. Ludwig, Gary W Meyer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Given a single reference stimulus, test stimuli can be sorted with respect to perceptual similarity to this anchor stimulus. Aggregated ranks can then be computed from multiple sort sequences. This ordinal scaling provides an estimate of perceptible differences and can be used to develop and test predictive models. In this paper we propose the use of graph-based methods visualizing experimental data and computing aggregated ranks. Specifically, perceptual similarity is expressed as a sort sequence graph in which nodes are stimuli and weighted edges are the frequency of the corresponding ranks. This graph is also oriented in that it has a start, the reference stimuli, and an end, the least similar stimuli. The Schulze method or the 'strongest path' computation is used for rank aggregation. This analysis is explored in the context of two appearance experiments: the first using solid colors and the second using renderings of 3D printed stimuli varying in multiple appearance attributes. For the second experiment with the renderings of 3D printed stimuli we then use Kendall Τ b values to assess a simple model based on mean CIELAB color differences. We find that the underlying sorting task is efficient and intuitive. Furthermore, the graph-based formulation of perceptual similarity allows the application of network analysis and graph theory to the study of visual appearance. New analyses are also possible, such as outlier detection using the sort sequences that are the inverse of the Schulze solution or approximately the 'wrongest path'.

Original languageEnglish (US)
Title of host publicationCIC 2018 - 26th Color and Imaging Conference
Subtitle of host publicationColor Science and Engineering Systems, Technologies, and Applications, Technical Papers and Proceedings
PublisherSociety for Imaging Science and Technology
Pages365-370
Number of pages6
ISBN (Electronic)9780892083374
StatePublished - Jan 1 2018
Event26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, CIC 2018 - Vancouver, Canada
Duration: Nov 12 2018Nov 16 2018

Publication series

NameFinal Program and Proceedings - IS and T/SID Color Imaging Conference
Volume2018-November
ISSN (Print)2166-9635
ISSN (Electronic)2169-2629

Other

Other26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, CIC 2018
CountryCanada
CityVancouver
Period11/12/1811/16/18

Fingerprint

classifying
Anchors
Sorting
stimuli
Color
Graph theory
Electric network analysis
Agglomeration
Experiments
graph theory
color
network analysis
formulations
scaling
estimates

Cite this

Moroney, N., Tastl, I., Gottwals, M., Ludwig, M., & Meyer, G. W. (2018). Single anchor sorting of visual appearance as an oriented graph. In CIC 2018 - 26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, Technical Papers and Proceedings (pp. 365-370). (Final Program and Proceedings - IS and T/SID Color Imaging Conference; Vol. 2018-November). Society for Imaging Science and Technology.

Single anchor sorting of visual appearance as an oriented graph. / Moroney, N.; Tastl, I.; Gottwals, M.; Ludwig, M.; Meyer, Gary W.

CIC 2018 - 26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, Technical Papers and Proceedings. Society for Imaging Science and Technology, 2018. p. 365-370 (Final Program and Proceedings - IS and T/SID Color Imaging Conference; Vol. 2018-November).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Moroney, N, Tastl, I, Gottwals, M, Ludwig, M & Meyer, GW 2018, Single anchor sorting of visual appearance as an oriented graph. in CIC 2018 - 26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, Technical Papers and Proceedings. Final Program and Proceedings - IS and T/SID Color Imaging Conference, vol. 2018-November, Society for Imaging Science and Technology, pp. 365-370, 26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, CIC 2018, Vancouver, Canada, 11/12/18.
Moroney N, Tastl I, Gottwals M, Ludwig M, Meyer GW. Single anchor sorting of visual appearance as an oriented graph. In CIC 2018 - 26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, Technical Papers and Proceedings. Society for Imaging Science and Technology. 2018. p. 365-370. (Final Program and Proceedings - IS and T/SID Color Imaging Conference).
Moroney, N. ; Tastl, I. ; Gottwals, M. ; Ludwig, M. ; Meyer, Gary W. / Single anchor sorting of visual appearance as an oriented graph. CIC 2018 - 26th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications, Technical Papers and Proceedings. Society for Imaging Science and Technology, 2018. pp. 365-370 (Final Program and Proceedings - IS and T/SID Color Imaging Conference).
@inproceedings{b08dc72d30574e84a1215567a3cd0634,
title = "Single anchor sorting of visual appearance as an oriented graph",
abstract = "Given a single reference stimulus, test stimuli can be sorted with respect to perceptual similarity to this anchor stimulus. Aggregated ranks can then be computed from multiple sort sequences. This ordinal scaling provides an estimate of perceptible differences and can be used to develop and test predictive models. In this paper we propose the use of graph-based methods visualizing experimental data and computing aggregated ranks. Specifically, perceptual similarity is expressed as a sort sequence graph in which nodes are stimuli and weighted edges are the frequency of the corresponding ranks. This graph is also oriented in that it has a start, the reference stimuli, and an end, the least similar stimuli. The Schulze method or the 'strongest path' computation is used for rank aggregation. This analysis is explored in the context of two appearance experiments: the first using solid colors and the second using renderings of 3D printed stimuli varying in multiple appearance attributes. For the second experiment with the renderings of 3D printed stimuli we then use Kendall Τ b values to assess a simple model based on mean CIELAB color differences. We find that the underlying sorting task is efficient and intuitive. Furthermore, the graph-based formulation of perceptual similarity allows the application of network analysis and graph theory to the study of visual appearance. New analyses are also possible, such as outlier detection using the sort sequences that are the inverse of the Schulze solution or approximately the 'wrongest path'.",
author = "N. Moroney and I. Tastl and M. Gottwals and M. Ludwig and Meyer, {Gary W}",
year = "2018",
month = "1",
day = "1",
language = "English (US)",
series = "Final Program and Proceedings - IS and T/SID Color Imaging Conference",
publisher = "Society for Imaging Science and Technology",
pages = "365--370",
booktitle = "CIC 2018 - 26th Color and Imaging Conference",
address = "United States",

}

TY - GEN

T1 - Single anchor sorting of visual appearance as an oriented graph

AU - Moroney, N.

AU - Tastl, I.

AU - Gottwals, M.

AU - Ludwig, M.

AU - Meyer, Gary W

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Given a single reference stimulus, test stimuli can be sorted with respect to perceptual similarity to this anchor stimulus. Aggregated ranks can then be computed from multiple sort sequences. This ordinal scaling provides an estimate of perceptible differences and can be used to develop and test predictive models. In this paper we propose the use of graph-based methods visualizing experimental data and computing aggregated ranks. Specifically, perceptual similarity is expressed as a sort sequence graph in which nodes are stimuli and weighted edges are the frequency of the corresponding ranks. This graph is also oriented in that it has a start, the reference stimuli, and an end, the least similar stimuli. The Schulze method or the 'strongest path' computation is used for rank aggregation. This analysis is explored in the context of two appearance experiments: the first using solid colors and the second using renderings of 3D printed stimuli varying in multiple appearance attributes. For the second experiment with the renderings of 3D printed stimuli we then use Kendall Τ b values to assess a simple model based on mean CIELAB color differences. We find that the underlying sorting task is efficient and intuitive. Furthermore, the graph-based formulation of perceptual similarity allows the application of network analysis and graph theory to the study of visual appearance. New analyses are also possible, such as outlier detection using the sort sequences that are the inverse of the Schulze solution or approximately the 'wrongest path'.

AB - Given a single reference stimulus, test stimuli can be sorted with respect to perceptual similarity to this anchor stimulus. Aggregated ranks can then be computed from multiple sort sequences. This ordinal scaling provides an estimate of perceptible differences and can be used to develop and test predictive models. In this paper we propose the use of graph-based methods visualizing experimental data and computing aggregated ranks. Specifically, perceptual similarity is expressed as a sort sequence graph in which nodes are stimuli and weighted edges are the frequency of the corresponding ranks. This graph is also oriented in that it has a start, the reference stimuli, and an end, the least similar stimuli. The Schulze method or the 'strongest path' computation is used for rank aggregation. This analysis is explored in the context of two appearance experiments: the first using solid colors and the second using renderings of 3D printed stimuli varying in multiple appearance attributes. For the second experiment with the renderings of 3D printed stimuli we then use Kendall Τ b values to assess a simple model based on mean CIELAB color differences. We find that the underlying sorting task is efficient and intuitive. Furthermore, the graph-based formulation of perceptual similarity allows the application of network analysis and graph theory to the study of visual appearance. New analyses are also possible, such as outlier detection using the sort sequences that are the inverse of the Schulze solution or approximately the 'wrongest path'.

UR - http://www.scopus.com/inward/record.url?scp=85061053293&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061053293&partnerID=8YFLogxK

M3 - Conference contribution

T3 - Final Program and Proceedings - IS and T/SID Color Imaging Conference

SP - 365

EP - 370

BT - CIC 2018 - 26th Color and Imaging Conference

PB - Society for Imaging Science and Technology

ER -