Personal Time-Lapse

UIST 2024

Nhan Tran Ethan Yang Angelique Taylor Abe Davis
Cornell University, NY, USA
Paper MeCapture App Interactive Results
Teaser Image

We present a mobile augmented reality tool that uses custom 3D tracking, interactive visual feedback, and computational imaging to capture personal time-lapses. These time-lapses approximate long-term videos of a subject (typically part of the user's body) under consistent viewpoint, pose, and lighting, providing a convenient way to document and visualize long-term changes in the body, with many potential applications in remote healthcare and telemedicine.

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.

Video



Mobile App: MeCapture

Create Personal Time-Lapse with your phone

View on App Store

(Coming soon, pending Apple Review)

Tutorial (coming soon)

Some Interactive 3D results

Interactive
Interactive
Interactive
Interactive
Interactive

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.