%0 Book Section
%A Zahra, Anam
%A Martin, Pierre-Etienne
%A Bohn, Manuel
%A Haun, Daniel
%+ Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
The Leipzig School of Human Origins (IMPRS), Max Planck Institute for Evolutionary Anthropology, Max Planck Society
Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
%T Computer vision for analyzing children’s lived experiences :
%G eng
%U https://hdl.handle.net/21.11116/0000-000F-3951-6
%R 10.1007/978-3-031-47724-9_25
%D 2024
%* Review method: peer-reviewed
%X Abstract. Children’s social and physical environment plays a signifi-
cant role in their cognitive development. Therefore, children’s lived expe-
riences are important to developmental psychologists. The traditional
way of studying everyday experiences has become a bottleneck because
it relies on short recordings and manual coding. Designing a non-invasive
child-friendly recording setup and automating the coding process can
potentially improve the research standards by allowing researchers to
study longer and more diverse aspects of experience. We leverage mod-
ern computer vision tools and techniques to address this problem. We
present a simple and non-invasive video recording setup and collect ego-
centric data from children. We test the state-of-the-art object detectors
and observe that egocentric videos from children are a challenging prob-
lem, indicated by the low mean Average Precision of state-of-the-art.
The performance of these object detectors can be improved through fine-
tuning. Once accurate object detection has been achieved, other ques-
tions, such as human-object interaction and scene understanding, can
be answered. Developing an automatic processing pipeline may provide
an important tool for developmental psychologists to study variation in
everyday experience.
%K Egocentric computer vision; Cognitive development;
Object detection
%B Intelligent Systems and Applications: Lecture Notes in Networks and Systems : Proceedings of the 2023 Intelligent Systems Conference (IntelliSys), Volume 2
%E Arai, Kohei
%P 376 - 383
%I Springer Nature Switzerland
%C Cham
%@ 978-3-031-47723-2 978-3-031-47724-9