Transcoding V-PCC Point Cloud Streams in Real-time

doi:10.1145/3682062

Transcoding V-PCC Point Cloud Streams in Real-time

2025-09-12

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DOI：10.1145/3682062

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Dynamic Point Clouds are a representation for three-dimensional (3D) immersive media that allows users to freely navigate a scene while consuming the content. However, this comes at the cost of substantial data size, requiring efficient compression techniques to make point cloud videos accessible. Addressing this, Video-based Point Cloud Compression (V-PCC) projects points into 2D patches to compress video frames, leveraging the high compression efficiency of legacy video codecs and exploiting temporal correlations in the two-dimensional (2D) images. However, clustering and projecting points into meaningful 2D patches is computationally intensive, leading to high encoding latency in V-PCC. Applying adaptive streaming techniques, originating from traditional video streaming, multiplies the computational effort as multiple encodings of the same content are required. In this light, transcoding a compressed representation into lower qualities for dynamic adaptation to user requirements is gaining popularity.

Transcoding V-PCC Point Cloud Streams in Real-time

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