Scheuchenpflug, Rainer (1999) Predicting face similarity judgements with a computational model of face space. ACTA PSYCHOLOGICA, 100 (3). pp. 229-242. ISSN 0001-6918,
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Current models of face representation involve the notion of a high-dimensional face space. Computational models of face space based on principal components analysis (PCA) have been successfully used to predict human judgements of face sex or race. In this work the capability of PCA-based face spaces to predict human judgements of face similarity is examined. Three different paradigms were used. In Experiment 1 subjects learned face-name associations for 18 faces and identified these faces on tachistoscopic presentation. The number of confusions was used as a measure of face similarity. In Experiment 2 the same subjects subjectively rated the similarity or all 153 possible face pairs. In Experiment 3 reaction time to identify a face in an odd-man-out task was measured as an index of face similarity. These empirical measures were correlated with distance of the faces in PCA-based spaces of different dimensionalities. For Experiment;; 1 and 2 these correlations were highest for one-or two-dimensional face spaces (r = -0.27 v. -0.28). For Experiment 3 the correlation was highest for a space consisting of 13 dimensions (r = -0.51). Thus PCA-based spaces seem capable to predict human similarity judgements to some extent. Possible reasons for the differences in predictability between paradigms are discussed. (C) 1999 Elsevier Science B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | RECOGNITION; INVERSION; DIFFERENCE; WOMEN; RACE; MEN; face perception; stimulus similarity; cognitive processes |
| Subjects: | 100 Philosophy & psychology > 150 Psychology |
| Divisions: | Human Sciences > Institut für Psychologie |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 23 Nov 2022 06:38 |
| Last Modified: | 23 Nov 2022 06:38 |
| URI: | https://pred.uni-regensburg.de/id/eprint/48593 |
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