180 citations · 343 across the 11 of their papers we have counts for
11 papers
Embedded vs. Situated: An Evaluation of AR Facial Training Feedback
Avinash Ajit Nargund, Andrea M. Park, Tobias Höllerer +1
While augmented reality (AR) research demonstrates benefits of embedded visualizations for gross motor training, its applicability to facial exercises remains under-explored. Provi…
Dynamic Theater: Location-Based Immersive Dance Theater, Investigating User Guidance and Experience
You-Jin Kim, Joshua Lu, Tobias Höllerer
Dynamic Theater explores the use of augmented reality (AR) in immersive theater as a platform for digital dance performances. The project presents a locomotion-based experience tha…
Spatial Orchestra: Locomotion Music Instruments through Spatial Exploration
You-Jin Kim, Myungin Lee, Marko Peljhan +2
Spatial Orchestra demonstrates how easy it is to play musical instruments using basic input like natural locomotion, which is accessible to most. Unlike many musical instruments, o…
Reality Distortion Room: A Study of User Locomotion Responses to Spatial Augmented Reality Effects
You-Jin Kim, Andrew D. Wilson, Jennifer Jacobs +1
Reality Distortion Room (RDR) is a proof-of-concept augmented reality system using projection mapping and unencumbered interaction with the Microsoft RoomAlive system to study a us…
XARP Tools: An Extended Reality Platform for Humans and AI Agents
Arthur Caetano, Radha Kumaran, Kelvin Jou +2
Building XR-AI research prototypes requires navigating two largely separate ecosystems. Mainstream XR development relies on C#/C++ and game engines, while AI development is centere…
Comparing Zealous and Restrained AI Recommendations in a Real-World Human-AI Collaboration Task
Chengyuan Xu, Kuo-Chin Lien, Tobias Höllerer
When designing an AI-assisted decision-making system, there is often a tradeoff between precision and recall in the AI's recommendations. We argue that careful exploitation of this…
Augmentation Strategies for Learning with Noisy Labels
Kento Nishi, Yi Ding, Alex Rich +1
Imperfect labels are ubiquitous in real-world datasets. Several recent successful methods for training deep neural networks (DNNs) robust to label noise have used two primary techn…
ARbis Pictus: A Study of Language Learning with Augmented Reality
Adam Ibrahim, Brandon Huynh, Jonathan Downey +3
This paper describes "ARbis Pictus" --a novel system for immersive language learning through dynamic labeling of real-world objects in augmented reality. We describe a within-subje…
Automated Assistants to Identify and Prompt Action on Visual News Bias
Vishwajeet Narwal, Mohamed Hashim Salih, Jose Angel Lopez +4
Bias is a common problem in today's media, appearing frequently in text and in visual imagery. Users on social media websites such as Twitter need better methods for identifying bi…
Botivist: Calling Volunteers to Action Using Online Bots
Saiph Savage, Andres Monroy-Hernandez, Tobias Hollerer
To help activists call new volunteers to action, we present Botivist: a platform that uses Twitter bots to find potential volunteers and request contributions. By leveraging differ…
Tag Me Maybe: Perceptions of Public Targeted Sharing on Facebook
Saiph Savage, Andres Monroy-Hernandez, Kasturi Bhattacharjee +1
Social network sites allow users to publicly tag people in their posts. These tagged posts allow users to share to both the general public and a targeted audience, dynamically asse…