Tianyi Wang*, Xun Qian*, Fengming He, Xiyun Hu, Ke Huo, Yuanzhi Cao, Karthik Ramani
CAPturAR: An Augmented Reality Tool for Authoring Human-Involved Context-Aware Applications
In Proceedings of the 2020 UIST 33rd ACM User Interface Software and Technology Symposium

Capture111Recognition of human behavior plays an important role in context-aware applications. However, it is still a challenge for end-users to build personalized applications that accurately recognize their own activities. Therefore, we present CAPturAR, an in-situ programming tool that supports users to rapidly author context-aware applications by referring to their previous activities. We customize an AR head-mounted device with multiple camera systems that allow for non-intrusive capturing of user’s daily activities. During authoring, we reconstruct the captured data in AR with an animated avatar and use virtual icons to represent the surrounding environment. With our visual programming interface, users create human-centered rules for the applications and experience them instantly in AR. We further demonstrate four use cases enabled by CAPturAR. Also, we verify the effectiveness of the AR-HMD and the authoring workflow with a system evaluation using our prototype. Moreover, we conduct a remote user study in an AR simulator to evaluate the usability.

Tianyi Wang
About Tianyi Wang

Tianyi Wang is a Ph.D. student in the School of Mechanical Engineering at Purdue University. Before joining the C Design Lab, Tianyi received his bachelor’s degree from the Department of Precision Instrument in Tsinghua University, Beijing in 2016. Tianyi’s current research interests focus on utilizing the technology of robotics, augmented reality as well as deep learning in the area of Human-Computer Interaction.

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Posted in 2020, Fengming He, Karthik Ramani, Karthik Ramani, Ke Huo, Publications, Recent Publications, Tianyi Wang, Xun Qian, Yuanzhi Cao