Tianyi Wang

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.
InstruMentAR: Auto-Generation of Augmented Reality Tutorials for Operating Digital Instruments Through Recording Embodied

InstruMentAR: Auto-Generation of Augmented Reality Tutorials for Operating Digital Instruments Through Recording Embodied

Ziyi Liu, Zhengzhe Zhu, Enze Jiang, Feichi Huang, Ana Villanueva, Tianyi Wang, Xun Qian, Karthik Ramani
In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Augmented Reality tutorials, which provide necessary context by directly superimposing visual guidance on the physical referent, represent an effective way of scaffolding complex instrument operations. However, current AR tutorial authoring...

MechARspace: An Authoring System Enabling Bidirectional Binding of Augmented Reality with Toys in Real-time

MechARspace: An Authoring System Enabling Bidirectional Binding of Augmented Reality with Toys in Real-time

Zhengzhe Zhu, Ziyi Liu, Tianyi Wang, Youyou Zhang, Xun Qian, Pashin Farsak Raja, Ana Villanueva, Karthik Ramani
In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (pp. 1-16).

Augmented Reality (AR), which blends physical and virtual worlds, presents the possibility of enhancing traditional toy design. By leveraging bidirectional virtual-physical interactions between humans and the designed artifact, such AR-enhanced...

ARnnotate: An Augmented Reality Interface for Collecting Custom Dataset of 3D Hand-Object Interaction Pose Estimation

ARnnotate: An Augmented Reality Interface for Collecting Custom Dataset of 3D Hand-Object Interaction Pose Estimation

Xun Qian, Fengming He, Xiyun Hu, Tianyi Wang, Karthik Ramani
In Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (pp. 1-14)

Vision-based 3D pose estimation has substantial potential in hand-object interaction applications and requires user-specified datasets to achieve robust performance. We propose ARnnotate, an Augmented Reality (AR) interface enabling end-users to...

ScalAR: Authoring Semantically Adaptive Augmented Reality Experiences in Virtual Reality

ScalAR: Authoring Semantically Adaptive Augmented Reality Experiences in Virtual Reality

Xun Qian, Fengming He, Xiyun Hu, Tianyi Wang, Ananya Ipsita, and Karthik Ramani
In the Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Augmented Reality (AR) experiences tightly associate virtual contents with environmental entities. However, the dissimilarity of different environments limits the adaptive AR content behaviors under large-scale deployment. We propose ScalAR, an...

GesturAR: An Authoring System for Creating Freehand Interactive Augmented Reality Applications

GesturAR: An Authoring System for Creating Freehand Interactive Augmented Reality Applications

Tianyi Wang, Xun Qian, Fengming He, Xiyun Hu, Yuanzhi Cao, Karthik Ramani
In The 34th Annual ACM Symposium on User Interface Software and Technology (UIST '21)

Freehand gesture is an essential input modality for modern Augmented Reality (AR) user experiences. However, developing AR applications with customized hand interactions remains a challenge for end-users. Therefore, we propose GesturAR, an...

LightPaintAR: Assist Light Painting Photography with Augmented Reality

LightPaintAR: Assist Light Painting Photography with Augmented Reality

Tianyi Wang, Xun Qian, Fengming He, Karthik Ramani
In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

Light painting photos are created by moving light sources in mid-air while taking a long exposure photo. However, it is challenging for novice users to leave accurate light traces without any spatial guidance. Therefore, we present LightPaintAR, a...

AdapTutAR: An Adaptive Tutoring System for Machine Tasks in Augmented Reality

AdapTutAR: An Adaptive Tutoring System for Machine Tasks in Augmented Reality

Gaoping Huang*, Xun Qian*, Tianyi Wang, Fagun Patel, Maitreya Sreeram, Yuanzhi Cao, Karthik Ramani, and Alexander J. Quinn
In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Modern manufacturing processes are in a state of flux, as they adapt to increasing demand for flexible and self-configuring production. This poses challenges for training workers to rapidly master new machine operations and processes, i.e. machine...

CAPturAR: An Augmented Reality Tool for Authoring Human-Involved Context-Aware Applications

CAPturAR: An Augmented Reality Tool for Authoring Human-Involved Context-Aware Applications

Tianyi Wang*, Xun Qian*, Fengming He, Xiyun Hu, Ke Huo, Yuanzhi Cao, Karthik Ramani
In Proceedings of the 2020 UIST 33rd ACM User Interface Software and Technology Symposium

Recognition 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 Exploratory Study of Augmented Reality Presence for Tutoring Machine Tasks

An Exploratory Study of Augmented Reality Presence for Tutoring Machine Tasks

Yuanzhi Cao, Xun Qian, Tianyi Wang, Rachel Lee, Ke Huo, Karthik Ramani
In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Machine tasks in workshops or factories are often a compound sequence of local, spatial, and body-coordinated human-machine interactions. Prior works have shown the merits of video-based and augmented reality (AR) tutoring systems for local tasks....

Autonomous Robotic Exploration and Mapping of Smart Indoor Environments With UWB-IoT Devices

Autonomous Robotic Exploration and Mapping of Smart Indoor Environments With UWB-IoT Devices

Tianyi Wang, Ke Huo, Muzhi Han, Daniel McArthur, Ze An, David Cappeleri, and Karthik Ramani
In Proceedings of AAAI Spring Symposium Series 2020

The emerging simultaneous localization and mapping (SLAM) techniques enable robots with the spatial awareness of the physical world. However, such awareness remains at a geometric level. We propose an approach for quickly constructing a smart...