| CARVIEW |
Personal Time-Lapse
UIST 2024
Abstract
Our bodies are constantly in motion—from the bending of arms and legs to the less conscious movement of breathing, our precise shape and location change constantly. This can make subtler developments (e.g., the growth of hair, or the healing of a wound) difficult to observe. Our work focuses on helping users record and visualize this type of subtle, longer-term change. We present a mobile tool that combines custom 3D tracking with interactive visual feedback and computational imaging to capture personal time-lapse, which approximates longer-term video of the subject (typically, part of the capturing user's body) under a fixed viewpoint, body pose, and lighting condition. These personal time-lapses offer a powerful and detailed way to track visual changes of the subject over time. We begin with a formative study that examines what makes personal time-lapse so difficult to capture. Building on our findings, we motivate the design of our capture tool, evaluate this design with users, and demonstrate its effectiveness in a variety of challenging examples.
Research Video
Mobile App: MeCapture
For iPhones and iPads with TrueDepth camera
Tutorial: Create your first Personal Time-Lapse
Some Interactive 3D results
A user documented their hand's healing process over a month after an accidental cooking burn.
While tapering down from high-dose corticosteroids, a user tracked the progression of a bruise on their foot over a week, a common side effect of the medication.
Starting with a clean shave, a user captured their facial hair growth daily for over a month.
Another user documented their mustache regrowth journey with daily captures spanning more than a month.
The color transformation of white flowers was captured over 48 hours after adding food coloring to their water.
Citation
@inproceedings{tran2024personal,
title={Personal Time-Lapse},
author={Tran, Nhan and Yang, Ethan and Taylor, Angelique and Davis, Abe},
booktitle={Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology},
pages={1--13},
year={2024}
}
Acknowledgements
This work was partially supported by a National Science Foundation Faculty Early Career Development Grant under award #2340448. It was also partially supported by a generous gift from Meta. We also thank our study participants and testers, especially Xinrui Liu, for their help and feedback in developing our app.
We thank filmmaker and YouTuber Bálint Kolozsvári aka Kolo / Time Lapse for the fruitful discussion on how he created high quality timelapse videos in highly controlled settings.