Large Language Model (LLM)-based copilots have shown great potential in Extended Reality (XR) applications. However, the user faces challenges when describing the 3D environments to the copilots due to the complexity of conveying spatial-temporal...

Large Language Model (LLM)-based copilots have shown great potential in Extended Reality (XR) applications. However, the user faces challenges when describing the 3D environments to the copilots due to the complexity of conveying spatial-temporal...
Despite the growing demand for experienced Internet of Things (IoT) professionals across industrial establishments, most secondary education institutions do not offer a curriculum to empower students’ knowledge and skills in IoT. Enrichment...
Extended Reality (XR)-enabled headsets that overlay digital content onto the physical world, are gradually finding their way into our daily life. This integration raises significant concerns about privacy and access control, especially in shared...
Context-aware AR instruction enables adaptive and in-situ learning experiences. However, hardware limitations and expertise requirements constrain the creation of such instructions. With recent developments in Generative Artificial Intelligence...
This paper presents the Dual Neural Network (DuNN) method, a physics-driven numerical method designed to solve elliptic partial differential equations and systems using deep neural network functions and a dual formulation. The underlying elliptic...
Despite the recognized efficacy of immersive Virtual Reality (iVR) in skill learning, the design of iVR-based learning units by subject matter experts (SMEs) based on target requirements is severely restricted. This is partly due to a lack of...
Computer vision (CV) algorithms require large annotated datasets that are often labor-intensive and expensive to create. We propose AnnotateXR, an extended reality (XR) workflow to collect various high-fidelity data and auto-annotate it in a single...
With the advents in geometry perception and Augmented Reality (AR), end-users can customize Tangible User Interfaces (TUIs) that control digital assets using intuitive and comfortable interactions with physical geometries (e.g., edges and...
Advancements in embodied language models like PALM-E and RT-2 have significantly enhanced language-conditioned robotic manipulation. However, these advances remain predominantly focused on vision and language, often overlooking the pivotal role of...
We study the problem of estimating the body movements of a camera wearer from egocentric videos. Current methods for ego-body pose estimation rely on temporally dense sensor data, such as IMU measurements from spatially sparse body parts like the...
We introduce the Multi-Motion Discrete Diffusion Models (M2D2M), a novel approach for human motion generation from textual descriptions of multiple actions, utilizing the strengths of discrete diffusion models. This approach adeptly addresses the...
Skeleton-based action recognition has made significant advancements recently, with models like InfoGCN showcasing remarkable accuracy. However, these models exhibit a key limitation: they necessitate complete action observation prior to...
Table tennis stroke training is a critical aspect of player development. We designed a new augmented reality (AR) system, avaTTAR, for table tennis stroke training. The system provides both "on-body" (first-person view) and "detached" (third-person...
Peer influence plays a crucial role in promoting classroom participation, where behaviors from active students can contribute to a collective classroom learning experience. However, the presence of these active students depends on several...
We present AircraftVerse, a publicly available aerial vehicle design dataset. Aircraft design encompasses different physics domains and, hence, multiple modalities of representation. The evaluation of these cyber-physical system (CPS) designs...
Interacting Objects: A dataset of object-object interactions for richer dynamic scene representations Asim Unmesh, Rahul Jain, Jingyu Shi, V. K. Chaithanya Manam, Hyung-Gun Chi, Subramanian Chidambaram, Alexander J. Quinn, Karthik Ramani IEEE...
In this paper, we study the deep Ritz method for solving the linear elasticity equation from a numerical analysis perspective. A modified Ritz formulation using the H1/2(ΓD) norm is introduced and analyzed for linear elasticity equation in order to...
Predicting future action locations is vital for applications like human-robot collaboration. While some computer vision tasks have made progress in predicting human actions, accurately localizing these actions in future frames remains an area with...
Utilizing everyday objects as tangible proxies for Augmented Reality (AR) provides users with haptic feedback while interacting with virtual objects. Yet, existing methods focus on the attributes of the objects, constraining the possible proxies...
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...
Accurately estimating the human pose is an essential task for many applications in robotics. However, existing pose estimation methods suffer from poor performance when occlusion occurs. Recent advances in NLP have been very successful in...
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...
The rapid growth of Internet-of-Things (IoT) applications has generated interest from many industries and a need for graduates with relevant knowledge. An IoT system is comprised of spatially distributed interactions between humans and various...
Interaction in mid-air can be fatiguing. A model-based method to quantify cumulative subjective fatigue for such interaction was recently introduced in HCI research. This model separates muscle units into three states: active (MA) fatigued (MF) or...
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...
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...
Augmented/Virtual reality and video-based media play a vital role in the digital learning revolution to train novices in spatial tasks. However, creating content for these different media requires expertise in several fields. We present EditAR, a...
Interaction in mid-air can be fatiguing. A model-based method to quantify cumulative subjective fatigue for such interaction was recently introduced in HCI research. This model separates muscle units into three states: active (Ma) fatigued (Mf) or...
Over the past decade, augmented reality (AR) developers have explored a variety of approaches to allow users to interact with the information displayed on smart glasses and head-mounted displays (HMDs). Current interaction modalities such as...
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...
The US manufacturing industry is currently facing a welding workforce shortage which is largely due to inadequacy of widespread welding training. To address this challenge, we present a Virtual Reality (VR)-based training system aimed at...
Human skeleton-based action recognition offers a valuable means to understand the intricacies of human behavior because it can handle the complex relationships between physical constraints and intention. Although several studies have focused on...
Current times are accelerating new technologies to provide high-quality education for remote collaboration, as well as hands-on learning. This is particularly important in the case of laboratory-based classes, which play an essential role in STEM...
Wearable technologies draw on a range of disciplines, including fashion, textiles, HCI, and engineering. Due to differences in methodology, wearables researchers can experience gaps or breakdowns in values, goals, and vocabulary when collaborating....
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...
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...
Current hand wearables have limited customizability, they are loose-fit to an individual's hand and lack comfort. The main barrier in customizing hand wearables is the geometric complexity and size variation in hands. Moreover, there are different...
Augmented reality (AR) is a unique, hands-on tool to deliver information. However, its educational value has been mainly demonstrated empirically so far. In this paper, we present a modeling approach to provide users with mastery of a skill, using...
Distance learning is facing a critical moment finding a balance between high quality education for remote students and engaging them in hands-on learning. This is particularly relevant for project-based classrooms and makerspaces, which typically...
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...
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...