We propose a novel object-mediated hand interaction system that enables real-time operation with everyday objects on wearable augmented reality (AR) devices. Despite recent advances, both commercial and academic hand interaction techniques remain constrained, typically requiring external hardware or depending exclusively on bare-hand gestures. Motivated by these constraints, we developed an offloading framework that integrates a high-fidelity transformer-based 3D hand reconstruction model with a dynamic gesture recognition network powered by gated recurrent units (GRU). This architecture ensures stable and accurate gesture recognition even during interaction with physical objects. To evaluate its quantitative performance, we collected a custom dataset based on a predefined gesture set, achieving 93.0% accuracy in 5-fold cross-validation. The complete system implemented on Microsoft HoloLens 2 operates at a real-time framerate, and we further analyze the latency of each step in our framework. Through this interaction paradigm, users can experience immersive and intuitive AR in everyday environments with minimal disruption to natural action behavior. Our projects are available at https://github.com/kaist-uvrlab/UnifiedHOInteraction.

PublicationEvent-Based Referred Vibrotactile Feedback for Bare-Hand XR Interaction

We propose event-based vibrotactile feedback as an effective approach for enhancing bare-hand XR interaction, delivered through commodity smartwatches that users already wear. While controllers and haptic gloves provide rich tactile feedback, they introduce additional hardware that users must carry and wear throughout the day. Importantly, they interpose hardware between the user and the virtual world, occupying the hands, constraining finger motion, and undermining truly unobstructed bare-hand interaction. Our proposed approach delivers short discrete pulses at key manipulation moments such as object contact and state changes, providing tactile confirmation at the wrist without requiring additional hardware or disrupting finger movement. Two user studies with 26 participants demonstrate that this referred feedback significantly enhances user experience at either wrist placement, with 94% finding it helpful and particular benefits during complex tasks like knob rotation where haptic cues reduced visual attention demands. These findings establish design guidelines for integrating accessible haptics into everyday XR through personal devices, supporting broader adoption of natural hand interaction.

PublicationForceCtrl: Hand-Raycasting with User-Defined Pinch Force for Control-Display Gain Application

We present ForceCtrl, a novel 3D hand raycasting technique that enhances pointing precision based on control-display (CD) gain controlled with user-defined pinch force. We introduce a target-agnostic approach for refining raycasting precision, overcoming limitations in human motor accuracy. User-defined pinch force, detected with surface electromyography (sEMG), enables users to easily activate or deactivate CD gain during interaction. We propose three CD gain strategies and compare them through target selection and placement tasks. Our system reduces selection errors, placement jitters, and user workload, especially for distant targets in high-difficulty tasks. These results highlight the effectiveness of applying CD gain to hand raycasting and demonstrate the potential of user-defined pinch force as a robust input modality for precise hand interaction in AR/VR.

PublicationStreamlined Facial Data Collection based on Utterance and Emotional Data for Human-to-Avatar Reconstruction

This study explores a streamlined facial data collection method for conversational contexts, addressing the limitations of existing approaches that often require extensive datasets and prioritize technical metrics over user perception and experience. We systematically investigate which facial expression data are essential for reconstructing photorealistic avatars and how they can be captured efficiently. Our research employs a two-phase methodology to identify efficient facial data collection strategies and evaluate their effectiveness. In the first phase, we conduct facial data acquisition and evaluate reconstruction performance using utterance data and emotional data. In the second phase, we carry out a comprehensive user evaluation comparing three progressive conditions: utterance only, utterance and emotional data, and a control condition involving extensive data. Findings from 24 participants engaged in simulated face-to-face conversations reveal that targeted utterance and emotional data achieve comparable levels of perceived realism, naturalness, and telepresence, while reducing training time and data usage when compared to the extensive data collection approach. These results demonstrate that targeted data inputs can enable efficient avatar face reconstruction, offering practical guidelines for real-time applications such as AR/VR telepresence and highlighting the trade-off between data quantity and perceived quality.

PublicationVisuo-Tactile Feedback with Hand Outline Styles for Modulating Affective Roughness Perception

We propose a visuo-tactile feedback method that combines virtual hand visualization and fingertip vibrations to modulate affective roughness perception in VR. While prior work has focused on object-based textures and vibrotactile feedback, the role of visual feedback on virtual hands remains underexplored. Our approach introduces affective visual cues including line shape, motion, and color applied to hand outlines, and examines their influence on both affective responses (arousal, valence) and perceived roughness. Results show that sharp contours enhanced perceived roughness, increased arousal, and reduced valence, intensifying the emotional impact of haptic feedback. In contrast, color affected valence only, with red consistently lowering emotional positivity. These effects were especially noticeable at lower haptic intensities, where visual cues extended affective modulation into mid-level perceptual ranges. Overall, the findings highlight how integrating expressive visual cues with tactile feedback can enrich affective rendering and offer flexible emotional tuning in immersive VR interactions.