CustomizAR: Facilitating Interactive Exploration and Measurement of Adaptive 3D Designs
Chen Liang, Anhong Guo, Jeeeun Kim
DIS'22: ACM SIGCHI Conference on Designing Interactive Systems (DIS)
Session: Video Previews
Abstract
Online 3D model repositories such as Thingiverse offer millions of open-source designs that are shared for reuse and remix. Many of the designs are customizable to adapt to real-world objects upon personal needs of varying tasks and physical dimensions. However, it is challenging for novice users to discover such designs using text-based search queries, comprehend what each parameter means for customization, locate these parameters on the target objects for measuring values, and conduct measurements correctly. These challenges may cause the designs to be incorrectly adjusted, thus failing to function as expected and requiring the users to start over, which costs additional time and material. We present CustomizAR, a pipeline for facilitating the interactive exploration of adaptive designs and the measurement of real-world constraints to fabricate them correctly. CustomizAR supports the search and discovery of adaptive 3D designs using an object-centric graph-based data structure, and guides users through an interactive measurement process leveraging computer vision techniques. Our technical evaluations and user studies demonstrate that CustomizAR facilitates effective discovery, adjustment, and reuse of adaptive designs that are shared online.
DOI:: https://doi.org/10.1145/3532106.3534569
WEB:: https://dis.acm.org/2022/
30-second video previews of DIS 2022