The QEST (QoE evaluations for multi-cloud streaming) project is a cascade project of the EU project SPIRIT. The contribution of QEST is twofold. First, the impact of state-of-the-art point cloud compression (PCC) mechanisms (G-PCC and V-PCC) is evaluated on two recent and under-investigated head-mounted displays (HMDs), i.e., the Apple Vision Pro and the Meta Quest 3. To this aim, a subjective assessment is conducted to evaluate the Quality of Experience (QoE) of compressed and uncompressed point clouds (PCs) displayed on these devices. Second, an adaptive algorithm to stream multiple PCs compressed at different levels of detail (LoD) is designed and implemented to address the limitations of current approaches that only consider the streaming of single PCs. To reach this objective, a novel dataset of PCs of tourist points of interest is collected, which is used to create 3D scenes including multiple PCs compressed (using G-PCC and V-PCC) at different LoD. The QoE of these 3D scenes, displayed on the two aforementioned HMDs, is assessed by conducting a second subjective assessment. Based on the achieved subjective results, an adaptive streaming algorithm is defined, which can select the optimal LoD of each PC present in a 3D scene based on the user’s field of view (FoV), the number of PCs in the scene, the network capabilities, and the maximum number of points that can be rendered by the considered HMD.
Budget: 100.000 €
Funding: European Union (SPIRIT, 101070672)
Duration: April 2025 – October 2025
Research Areas: Immersive Multimedia and Metaverse, Quality of Experience
Principal Investigator: Simone Porcu