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The ability to detect phenotypic similarity or kinship in third-parties' faces is not perfect, but better than chance. Still, some humans are better than others at this task. Yet researchers in kinship detection have difficulties in building up large and diverse datasets of high-quality pictures of related persons. The current experiments tested a novel method for circumventing this difficulty by using morphing techniques in order to generate a wide array of stimuli derived from a limited number of individual pictures. Six experiments tested various stimuli (standard protocol, mirrored face, other-sex face, other-ethnicity face, other-expression face and antiface). Our benchmarks are the similarity or kinship scores achieved by participants when faced with pictures of real siblings. We show that all stimuli, except the antiface, elicit detection scores similar to those elicited by real pictures of actual siblings. In addition, by exploring different experiment parameters (simultaneous or sequential task, kinship or similarity task) and some individual characteristics, these experiments provide a better understanding of kinship detection in third parties. The validation of our new method will allow widening the range of available stimuli to the research community, and even to develop new ecologically relevant experimental protocols that are hardly or not feasible with veridical images. |
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