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/m²) 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.
ACM CHI Conference on Human Factors in Computing Systems