Applications of a compact session encoding for immersive WebVR/XR analytics

Within Cultural Heritage, capturing immersive VR sessions performed through HMDs in explorative 3D scenes may provide valuable insights on users' interactions and spatial affordances. Thanks to its recent specifcations (WebVR/WebXR) the Web represents an incredible opportunity to create accessible, interactive and usable frameworks for remote VR analysts. Immersive WebVR/XR analytics performed through common web browsers although, raise several challenges, including limited rendering resources, data exchange over the network and encoding/decoding computational workload. Furthermore, unexpected locations of a given 3D scene may receive users' interest: a volumetric approach is required to allow the remote VR analyst to fully understand 3D interactions performed within a virtual environment. This work presents results and applications of a compact, lightweight imagebased encoding model designed for remote VR analysts. The integration with existing open-source Front-Ends opens up several possibilities to create fertile ground for interactive and remote VR inspection of immersive sessions. Advantages of the approach are also shown within collaborative VR sessions, and how the analyst can easily extract volumetric attentional synchrony by performing basic 2D image operations