PaperToPlace: Transforming Instruction Documents into Spatialized and Context-Aware Mixed Reality Experiences

要旨

While paper instructions are one of the mainstream medium for sharing knowledge, consuming such instructions and translating them into activities are inefficient due to the lack of connectivity with physical environment. We present PaperToPlace, a novel workflow comprising an authoring pipeline, which allows the authors to rapidly transform and spatialize existing paper instructions into MR experience, and a consumption pipeline, which computationally place each instruction step at an optimal location that is easy to read and do not occlude key interaction areas. Our evaluations of the authoring pipeline with 12 participants demonstrated the usability of our workflow and the effectiveness of using a machine learning based approach to help extracting the spatial locations associated with each steps. A second within-subject study with another 12 participants demonstrates the merits of our consumption pipeline by reducing efforts of context switching, delivering the segmented instruction steps and offering the hands-free affordances.

著者
Chen Chen
University of California San Diego, La Jolla, California, United States
Cuong Nguyen
Adobe Research, San Francisco, California, United States
Jane Hoffswell
Adobe Research, Seattle, Washington, United States
Jennifer Healey
Adobe Research, San Jose, California, United States
Trung Bui
Adobe Research, San Jose, California, United States
Nadir Weibel
University of California San Diego, La Jolla, California, United States
論文URL

https://doi.org/10.1145/3586183.3606832

動画

会議: UIST 2023

ACM Symposium on User Interface Software and Technology

セッション: Reality Refined: Augmented Reality Techniques

Venetian Room
7 件の発表
2023-11-01 23:10:00
2023-11-02 00:50:00