EVENT CAMERAS FOR HUMANOID SOCIAL PERCEPTION: A SCOPING REVIEW OF FACIAL DYNAMICS AND DEPLOYMENT EVIDENCE

Event cameras are increasingly considered for humanoid human-robot interaction (HRI) because their asynchronous output can preserve fast facial micro-dynamics under motion blur and difficult illumination. The field lacks standardized protocols, covering sensor settings, event integration windows, and evaluation metrics, which limits quantitative comparison across studies and makes robot-mounted transfer uncertain. This PRISMA-ScR scoping review consolidates the emerging evidence through a six-layer taxonomy, spanning sensing to deployability. Across the charted literature, support is strongest for region of interest (ROI)/landmark front-end components and paired-capture supervision. In contrast, humanoid-critical factors, ego-motion quantification, still-user low-motion “signal starvation,” motion-generalization testing, and end-to-end timing, are rarely operationalized as explicit axes. We translate these gaps into a minimal benchmark and on-humanoid dataset direction centered on Facial Action Units and operational engagement proxies, with paired RGB-event capture, logged motion metadata, and reproducible reporting of integration settings and latency.