Abstract
Recent research has observed two basic eye movement patterns in face recognition: central (fixations are around the nose) and triangular (fixations are on the two eyes and mouth). Here we aim to examine the link between eye movement patterns and engagement of global/local attention. Eye movements of Asian participants were monitored in an old/new face judgment task. Participants received global or local priming by matching two Navon stimuli at the global or local level respectively between the study and recognition phase, and in the beginning of each recognition trial. A hidden Markov model (HMM) based approach (Chuk, Chan, & Hsiao, 2014) was used to analyze the eye movement data. We modeled each participant's eye movement pattern with an HMM, and clustered these HMMs into two general patterns according to their similarities; one of the resulting patterns resembled the central (holistic) pattern, whereas the other resembled the triangular (analytic) pattern (Figure 1). We then calculated the log likelihoods of each participant's eye movement pattern belonging to the two patterns with and without priming. The results showed that compared with the baseline (no priming) condition, local priming significantly increased the likelihood of participants’ eye movement pattern being classified as the analytic pattern, whereas global priming did not significantly change the likelihood (Figure 2). This effect can also be seen in fixation maps (Figure 3), although it is relatively harder to interpret the differences. In addition, participants had better recognition performance after local priming than global priming (Figure 4), suggesting an advantage of the analytic strategy in face recognition. Thus, our results suggest that the holistic pattern is linked to engagement of global attention/global information processing, whereas the analytic pattern represents the use of local attention/featural-based processing. Local priming helps participants direct attention to facial features and may consequently enhance recognition performance.
Meeting abstract presented at VSS 2015