An asynchronous, hands-off workflow for looking time experiments with infants.

The study of infant gaze has long been a key tool for understanding the developing mind. However, labor-intensive data collection and processing limit the speed at which this understanding can be advanced. Here, we demonstrate an asynchronous workflow for conducting violation-of-expectation (VoE) experiments, which is fully "hands-off" for the experimenter.

iCatcher+: Robust and Automated Annotation of Infants' and Young Children's Gaze Behavior From Videos Collected in Laboratory, Field, and Online Studies.

Technological advances in psychological research have enabled large-scale studies of human behavior and streamlined pipelines for automatic processing of data. However, studies of infants and children have not fully reaped these benefits because the behaviors of interest, such as gaze duration and direction, still have to be extracted from video through a laborious process of manual annotation, even when these data are collected online. Recent advances in computer vision raise the possibility of automated annotation of these video data.