The BabyView Camera

An overview of a new camera designed to measure egocentric visual experience in early childhood.

View the Project on GitHub langcog/babyview


About the BabyView

The BabyView camera is designed to collect high-resolution, at-home egocentric video data from children 6 - 30 months of age. The camera consists of a rotated GoPro Black Bones camera attached to a lightweight baby safety helmet using a custom 3D printed mount and attached to a rechargeable 9V battery. The BabyView camera was designed in collaboration with Daylight, Inc., a product-design firm in San Francisco, CA, and and is the result of more than a year of prototyping.

All design documentation, safety testing protocols, assembly instructions (with detailed photos), pilot data, data management protocols, and sample participant instructions can be found on the BabyView OSF page.

Our paper detailing our design process is now out in Behavioral Research Methods and can be found here. An open-access version is on PsyArXiv and can be found here. A detailed instruction manual that we give to parents in linked on the OSF page but can also be found here.

Camera overview


Building your own BabyView

Here is a detailed guide . to assembling your own BabyView Camera, as well as a bill of materials . for each component; the custom mounts will need to be 3D printed (see the BabyView OSF page for CAD files).

Camera choice

Our goal was to capture a toddler’s field of view and their interactions as accurately as possible while also providing head tracking data. We found that the GoPro Hero Bones meet these needs with a ~100°+ FOV, Gyroscope, accelerometer, high resolution video and recording time up to 45-60 with this current battery choice. Data is recorded onto micro SD cards which can hold up to 256G. During our experimentation with the GoPros, we determined that orienting the camera vertically at an angle neutral to the face place of the child was preferable because it enables the camera to capture both adult faces and objects within a child’s hands in the same image; see example images below.

Contact and Acknowledgements


Bria Long1, Sarah Goodin2, George Kachergis1, Virginia A. Marchman1, Samaher F. Radwan1, Robert Z. Sparks 1, Violet Xiang1, Chengxu Zhuang1, Oliver Hsu2, Brett Newman2, Daniel L. K. Yamins1,3, Michael C. Frank1

1 Department of Psychology, Stanford University 2 Daylight Design 3 Department of Computer Science, Stanford University

Research and development of the BabyView was supported by a generous gift from The Schmidt Futures Foundation (

For more information, contact Michael Frank.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License. It can be shared and adapted, but you must acknowledge the original by citing the paper above.