Quality of Experience Evaluations for Multi-cloud Streaming

Point clouds are widely used in immersive multimedia systems because they can be acquired in real time using sensors like LiDAR (Light Detection and Ranging) or Time-of-Flight (ToF) cameras, which makes them ideal for building realistic and interactive 3D experiences. However, their large size introduces challenges for compression and streaming, especially in complex scenes with multiple objects viewed through head-mounted displays (HMDs). This paper presents two experimental applications developed for two recent underinvestigated HMDs: the Apple Vision Pro and Meta Quest 3. The first application allows users to view compressed dynamic point clouds and rate their perceived visual Quality of Experience (QoE) using a simple hand-based interface. The second application focuses on complex 3D scenes with multiple point clouds and supports the development of an adaptive streaming algorithm that optimizes the QoE based on the user’s view and system constraints. These tools aim to support future research on immersive content delivery in extended reality (XR), with possible applications in tourism and cultural heritage.