Fengming He

Fengming He

Fengming He is a Ph.D. student in the School of Electrical and Computer Engineering at Purdue University. She received her B.S. degree in Electrical and Computer Engineering in 2017 from Wuhan University, China. Her research interest includes computer vision, machine learning and its application to Augmented Reality (AR) and Human-Computer Interaction (HCI).
Ubi Edge: Authoring Edge-Based Opportunistic Tangible User Interfaces in Augmented Reality

Ubi Edge: Authoring Edge-Based Opportunistic Tangible User Interfaces in Augmented Reality

Fengming He, Xiyun Hu, Jingyu Shi, Xun Qian, Tianyi Wang, Karthik Ramani
In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Edges are one of the most ubiquitous geometric features of physical objects. They provide accurate haptic feedback and easy-totrack features for camera systems, making them an ideal basis for Tangible User Interfaces (TUI) in Augmented Reality...

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...

ProcessAR: An augmented reality-based tool to create in-situ procedural 2D/3D AR Instructions

ProcessAR: An augmented reality-based tool to create in-situ procedural 2D/3D AR Instructions

Subramanian Chidambaram, Hank Huang, Fengming He, Xun Qian, Ana M Villanueva, Thomas S Redick, Wolfgang Stuerzlinger, Karthik Ramani
In Proceedings of the Designing Interactive Systems Conference

Augmented reality (AR) is an efficient form of delivering spatial information and has great potential for training workers. However, AR is still not widely used for such scenarios due to the technical skills and expertise required to create...

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...

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,...