Cargando…

The diversity rank-score function for combining human visual perception systems

There are many situations in which a joint decision, based on the observations or decisions of multiple individuals, is desired. The challenge is determining when a combined decision is better than each of the individual systems, along with choosing the best way to perform the combination. It has be...

Descripción completa

Detalles Bibliográficos
Autores principales: Schweikert, Christina, Mulia, Darius, Sanchez, Kilby, Hsu, D. Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883166/
https://www.ncbi.nlm.nih.gov/pubmed/27747600
http://dx.doi.org/10.1007/s40708-016-0037-3
_version_ 1782434224177938432
author Schweikert, Christina
Mulia, Darius
Sanchez, Kilby
Hsu, D. Frank
author_facet Schweikert, Christina
Mulia, Darius
Sanchez, Kilby
Hsu, D. Frank
author_sort Schweikert, Christina
collection PubMed
description There are many situations in which a joint decision, based on the observations or decisions of multiple individuals, is desired. The challenge is determining when a combined decision is better than each of the individual systems, along with choosing the best way to perform the combination. It has been shown that the diversity between systems plays a role in the performance of their fusion. This study involved several pairs of people, each viewing an event and reporting an observation, along with their confidence level. Each observer is treated as a visual perception system, and hence an associated scoring system is created based on the observer’s confidence. A diversity rank-score function on a set of observation pairs is calculated using the notion of cognitive diversity between two scoring systems in the combinatorial fusion analysis framework. The resulting diversity rank-score function graph provides a powerful visualization tool for the diversity variation among a set of system pairs, helping to identify which system pairs are most likely to show improved performance with combination.
format Online
Article
Text
id pubmed-4883166
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-48831662016-08-19 The diversity rank-score function for combining human visual perception systems Schweikert, Christina Mulia, Darius Sanchez, Kilby Hsu, D. Frank Brain Inform Article There are many situations in which a joint decision, based on the observations or decisions of multiple individuals, is desired. The challenge is determining when a combined decision is better than each of the individual systems, along with choosing the best way to perform the combination. It has been shown that the diversity between systems plays a role in the performance of their fusion. This study involved several pairs of people, each viewing an event and reporting an observation, along with their confidence level. Each observer is treated as a visual perception system, and hence an associated scoring system is created based on the observer’s confidence. A diversity rank-score function on a set of observation pairs is calculated using the notion of cognitive diversity between two scoring systems in the combinatorial fusion analysis framework. The resulting diversity rank-score function graph provides a powerful visualization tool for the diversity variation among a set of system pairs, helping to identify which system pairs are most likely to show improved performance with combination. Springer Berlin Heidelberg 2016-02-15 /pmc/articles/PMC4883166/ /pubmed/27747600 http://dx.doi.org/10.1007/s40708-016-0037-3 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Schweikert, Christina
Mulia, Darius
Sanchez, Kilby
Hsu, D. Frank
The diversity rank-score function for combining human visual perception systems
title The diversity rank-score function for combining human visual perception systems
title_full The diversity rank-score function for combining human visual perception systems
title_fullStr The diversity rank-score function for combining human visual perception systems
title_full_unstemmed The diversity rank-score function for combining human visual perception systems
title_short The diversity rank-score function for combining human visual perception systems
title_sort diversity rank-score function for combining human visual perception systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883166/
https://www.ncbi.nlm.nih.gov/pubmed/27747600
http://dx.doi.org/10.1007/s40708-016-0037-3
work_keys_str_mv AT schweikertchristina thediversityrankscorefunctionforcombininghumanvisualperceptionsystems
AT muliadarius thediversityrankscorefunctionforcombininghumanvisualperceptionsystems
AT sanchezkilby thediversityrankscorefunctionforcombininghumanvisualperceptionsystems
AT hsudfrank thediversityrankscorefunctionforcombininghumanvisualperceptionsystems
AT schweikertchristina diversityrankscorefunctionforcombininghumanvisualperceptionsystems
AT muliadarius diversityrankscorefunctionforcombininghumanvisualperceptionsystems
AT sanchezkilby diversityrankscorefunctionforcombininghumanvisualperceptionsystems
AT hsudfrank diversityrankscorefunctionforcombininghumanvisualperceptionsystems