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Chantal L. Lemieux, Elizabeth A. Nelson, Charles A. Collin; Eye Movement Patterns Suggest Different Facial Features are Most Informative at Different Spatial Frequencies. Journal of Vision 2013;13(9):399. doi: 10.1167/13.9.399.
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© ARVO (1962-2015); The Authors (2016-present)
While many studies have shown that a middle band of spatial frequencies (SF) is most useful for face recognition, others have pointed out that the most informative SF ranges vary depending on location on the face. In two experiments, we examined variations in the utility of different SFs across the face by measuring eye movements during an old/new recognition task using spatially filtered faces. Eye movements were recorded using the Eyelink II (SR-Research.com). In Experiment 1, we measured 32 subjects' eye movements during the learning phase of the old/new task; In Experiment 2 we examined 15 subjects' eye movements during the retrieval phase of the same task. Stimuli were 32 faces filtered to preserve 11 SF bands across the spectrum (bandwidth 2 octaves), plus an unfiltered baseline condition. Twelve areas of interest (AOIs) were defined for each face, and total fixation time was analyzed across AOI and SF. Results show that low SFs elicited more fixations on medial AOIs such as nose, forehead and chin. This may indicate a tendency towards holistic processing, whereby fixation on these features represents an attempt to take in the entire face. In contrast, high SFs elicited more fixations on inner features, such as eyes and mouth, suggesting greater featural processing. Analysis of gaze transitions across AOIs show that fixation patterns vary across SF. Specifically, subjects transition more between the inner features, and exhibit more transitions in general, when examining high SF faces. When looking at low SF faces, transitions tend to be few, and to stay within medial features such as nose, nasion and forehead. Our results are compatible with previous work suggesting that the useful SFs vary by face part. We also find evidence suggesting that low and high SFs respectively support holistic and featural processing.
Meeting abstract presented at VSS 2013
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