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dc.contributor.authorSivagnanasundaram, Navaneethan
dc.contributor.authorChaparro, Alex
dc.contributor.authorPalmer, Evan M.
dc.identifier.citationSivagnanasundaram, N., Chaparro, A., & Palmer, E.M. (2013). Evaluation of the presence of a face search advantage in Chernoff faces. Proceedings from 2013 Human Factors and Ergonomics Society Annual Meeting, San Diego, California, September 30-October 4, 2013.
dc.identifier.otherdoi: 10.1177/1541931213571358
dc.descriptionClick on the DOI link below to access the article (may not be free).
dc.description.abstractChernoff faces (Chernoff, 1973) are an early attempt at large scale multivariate data representation and are based on underlying assumptions that have not been empirically tested. This study investigated i) whether data coded as Chernoff faces benefit from face perception, and ii) whether each feature of a Chernoff face is equally salient. We tested four pairs of oppositely coded Chernoff faces (e.g. smile, frown) in an oddball search paradigm with set sizes of 5, 10 and 15. To evaluate whether face perception aided search, we used a control condition with inverted faces, a manipulation known to diminish holistic face processing. Equivalent search efficiencies for upright and inverted Chernoff faces demonstrates that they do not receive any significant benefit from face perception. Additionally, none of the features tested together produced significantly different search efficiencies from one another. It also appears that overall Chernoff faces do not allow for particularly efficient visual search.
dc.relation.ispartofseriesHuman Factors and Ergonomics Society Annual Meeting
dc.titleEvaluation of the presence of a face search advantage in Chernoff faces
dc.typeConference paper
dc.rights.holderHuman Factors and Ergonomics Society, Inc.

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