SVATA: A Spatial Visual Attention Tracking and Analysis Platform for Embodied Cognition Research

Understanding spatial visual attention is important for embodied cognition research, yet practical platforms for 3D attention analysis remain limited. We present SVATA—Spatial Visual Attention Tracking and Analysis, an open-source platform that supports an end-to-end workflow for collecting, analyzing, and visualizing world-referenced gaze-and-movement data within a 3D spatial context. SVATA maps multimodal signals (gaze, head, position) onto reconstructed geometry and computes a physiologically informed Average Focus Weight ($AFW/m^{2}$) metric as a proxy for overt visual focus. This representation supports structured analysis and multidimensional visualization of spatial viewing patterns. We evaluated SVATA through an in-the-wild museum deployment with 78 visitors and an expert study with seven prospective users; the results suggest its feasibility and perceived utility for analyzing spatial viewing behavior in embodied cognition research.