ARFlow: a framework for simplifying AR experimentation workflow

Python source

This is an external project that uses Rerun as a core component.

External project presentation external-project-presentation

ARFlow is designed to lower the barrier for AR researchers to evaluate ideas in hours instead of weeks or months, following:

Efficient AR experiment data collection from various data sources, including camera, depth sensors, and IMU sensors with an efficient thin mobile client.
Flexible AR runtime data management with real-time visualization (powered by Rerun).
Easy integration with existing AR research projects without breaking the experimentation logic.

Watch our demo video:

Get started get-started

Please see the original project repo, and refer to the individual server and client installation guides.

Citation citation

Please add the following citation in your publication if you used our code for your research project.

@inproceedings{zhao2024arflow,
author = {Zhao, Yiqin and Guo, Tian},
title = {Demo: ARFlow: A Framework for Simplifying AR Experimentation Workflow},
year = {2024},
isbn = {9798400704970},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3638550.3643617},
doi = {10.1145/3638550.3643617},
abstract = {The recent advancement in computer vision and XR hardware has ignited the community's interest in AR systems research. Similar to traditional systems research, the evaluation of AR systems involves capturing real-world data with AR hardware and iteratively evaluating the targeted system designs [1]. However, it is challenging to conduct scalable and reproducible AR experimentation [2] due to two key reasons. First, there is a lack of integrated framework support in real-world data capturing, which makes it a time-consuming process. Second, AR data often exhibits characteristics, including temporal and spatial variations, and is in a multi-modal format, which makes it difficult to conduct controlled evaluations.},
booktitle = {Proceedings of the 25th International Workshop on Mobile Computing Systems and Applications},
pages = {154},
numpages = {1},
location = {, San Diego, CA, USA, },
series = {HOTMOBILE '24}
}