Personal Time-Lapse

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.

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Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3654777.3676383
Citations
3
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
3.90
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article

Personal Time-Lapse

Abe Davis, Ethan Yang, Angelique Taylor, Nhan Tran
3 citations
Robotics and Sensor-Based Localization
3.90
article

Personal Time-Lapse

Abe Davis, Ethan Yang, Angelique Taylor, Nhan Tran
article en
3 citations

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.

Cornell University (US)
Openalex Percentile: Top 6%
Robotics and Sensor-Based Localization
3.90
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