AI RESEARCH
Face versus Body Tracking for Human-Robot Interaction: An Egocentric Dataset
arXiv CS.CV
•
ArXi:2606.03694v1 Announce Type: cross To enable meaningful human-robot interaction (HRI), a robot must continuously assess engagement by consistently tracking users over time. State-of-the-art computer vision models, however, are heavily optimized for surveillance or autonomous driving. A social robot faces distinct egocentric challenges, such as humans bouncing, obstructing each other, or leaving the frame. Frequent identity switches (IDSW) cause the robot to lose its footing mid-conversation. To address this, we.