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...
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...
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...
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...
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...