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Standards Development
This project will define bitstream syntax and semantics of encoded point clouds, and decoding procedure to reconstruct point clouds.
Solid point clouds are dense 3D representations of object and scene surfaces, capturing highresolution geometry along with rich visual attributes. They are increasingly used in advanced applications such as augmented reality (AR), virtual reality (VR), 3D remote collaboration, and medical imaging. The density and precision of this content result in very large data volumes, making efficient compression essential for storage, transmission, and real-time interaction. MPEG’s Geometry-based Point Cloud Compression (G-PCC) standard, published in March 2023, offers a versatile solution capable of compressing both static and dynamic point clouds. However, G-PCC was originally designed with sparse point clouds in mind, such as those captured by LiDAR sensors. While it can encode dense point clouds, its performance in such cases is limited due to the absence of tools specifically tailored for high-density spatial and temporal structures. For example, G-PCC lacks dense intra prediction mechanisms and does not include local motion compensation optimized for highresolution, continuous surfaces. To address these limitations, the proposed new work item introduces a dedicated compression standard for solid (i.e., dense) point clouds. The goal is to significantly improve coding efficiency for this class of content while enabling real-time decoding and easier integration into portable, low-power, and embedded systems. The architecture will emphasize reduced complexity and HW/SW-friendly design, making it well-suited for deployment in head-mounted displays, AR glasses, mobile devices, and medical imaging equipment.
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