The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology

要旨

Motion capture systems, used across various domains, make body representations concrete through technical processes. We argue that the measurement of bodies and the validation of measurements for motion capture systems can be understood as social practices. By analyzing the findings of a systematic literature review (N=278) through the lens of social practice theory, we show how these practices, and their varying attention to errors, become ingrained in motion capture design and innovation over time. Moreover, we show how contemporary motion capture systems perpetuate assumptions about human bodies and their movements. We suggest that social practices of measurement and validation are ubiquitous in the development of data- and sensor-driven systems more broadly, and provide this work as a basis for investigating hidden design assumptions and their potential negative consequences in human-computer interaction.

受賞
Honorable Mention
著者
Emma Harvey
Cornell University, Ithaca, New York, United States
Hauke Sandhaus
Cornell University, Ithaca, New York, United States
Abigail Jacobs
University of Michigan, Ann Arbor, Michigan, United States
Emanuel Moss
Intel Labs, Hillsboro, Oregon, United States
Mona Sloane
University of Virginia, Charlottesville, Virginia, United States
論文URL

https://doi.org/10.1145/3613904.3642004

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Politics of Datasets

316C
5 件の発表
2024-05-14 18:00:00
2024-05-14 19:20:00