Exploration of factors affecting webcam-based automated gaze coding.

ABSTRACT: Online experiments have been transforming the field of behavioral research, enabling researchers to increase sample sizes, access diverse populations, lower the costs of data collection, and promote reproducibility. The field of developmental psychology increasingly exploits such online testing approaches. Since infants cannot give explicit behavioral responses, one key outcome measure is infants' gaze behavior. In the absence of automated eyetrackers in participants' homes, automatic gaze classification from webcam data would make it possible to avoid painstaking manual coding. However, the lack of a controlled experimental environment may lead to various noise factors impeding automatic face detection or gaze classification. We created an adult webcam dataset that systematically reproduc

SUBMITTER: Hagihara H 

PROVIDER: S-EPMC11362184 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature