Personal Time-Lapse

要旨

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.

著者
Nhan Tran
Cornell University, Ithaca, New York, United States
Ethan Yang
Cornell University, Ithaca, New York, United States
Angelique Taylor
Cornell University, New York City, New York, United States
Abe Davis
Cornell Tech, Cornell University, New York, New York, United States
論文URL

https://doi.org/10.1145/3654777.3676383

動画

会議: UIST 2024

ACM Symposium on User Interface Software and Technology

セッション: 2. Vision-based UIs

Westin: Allegheny 2
4 件の発表
2024-10-15 19:40:00
2024-10-15 20:40:00