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The field of developmental psychology increasingly exploits such online testing approaches. Since infants cannot give explicit behavioral responses, one key outcome measure is infants\u2019 gaze behavior. In the absence of automated eyetrackers in participants\u2019 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 reproduced noise factors from infant webcam studies which might affect automated gaze coding accuracy. We varied participants\u2019 left-right offset, distance to the camera, facial rotation, and the direction of the lighting source. Running two state-of-the-art classification algorithms (iCatcher+ and OWLET) revealed that facial detection performance was particularly affected by the lighting source, while gaze coding accuracy was consistently affected by the distance to the camera and lighting source. Morphing participants\u2019 faces to be unidentifiable did not generally affect the results, suggesting facial anonymization could be used when making online video data publicly available, for purposes of further study and transparency. Our findings will guide improving study design for infant and adult participants during online experiments. Moreover, training algorithms using our dataset will allow researchers to improve robustness and allow developmental psychologists to leverage online testing more efficiently.<\/jats:p>","DOI":"10.3758\/s13428-024-02424-1","type":"journal-article","created":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T16:14:51Z","timestamp":1714580091000},"page":"7374-7390","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Exploration of factors affecting webcam-based automated gaze coding"],"prefix":"10.3758","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3316-600X","authenticated-orcid":false,"given":"Hiromichi","family":"Hagihara","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7484-6995","authenticated-orcid":false,"given":"Lorijn","family":"Zaadnoordijk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5234-7415","authenticated-orcid":false,"given":"Rhodri","family":"Cusack","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nanako","family":"Kimura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9580-4500","authenticated-orcid":false,"given":"Sho","family":"Tsuji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,1]]},"reference":[{"key":"2424_CR1","unstructured":"Amazon. 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