Publication

Temporal Conditional Coding for Dynamic Point Cloud Geometry Compression

Touradj Ebrahimi
2024
Conference Papers

Abstract

Point clouds allow for the representation of 3D multimedia content as a set of disconnected points in space. Their inher- ent irregular geometric nature poses a challenge to efficient compression, a critical operation for both storage and trans- mission. This paper proposes a VAE-inspired codec tailored for dynamic point cloud geometry compression, taking ad- vantage of a temporal autoregressive hyperprior to enhance compression performance. Specifically, features derived from adjacent point cloud frames help build a hyperprior for con- ditional entropy coding. Sparse convolutions are leveraged to reach higher computational efficiency when compared to 3D dense convolutions. Remarkably, the proposed approach achieves an average 60.2% BD-rate gain against the contem- porary V-PCC compression standard from MPEG.

Official source

https://infoscience.epfl.ch/entities/publication/d0c41b8b-6f5d-4bbc-bbef-b9b7a87f30db

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Touradj Ebrahimi
2024
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/d0c41b8b-6f5d-4bbc-bbef-b9b7a87f30db

About this result

Related concepts (28)

Data compression

In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information.

Image compression

Image compression is a type of data compression applied to s, to reduce their cost for storage or transmission. Algorithms may take advantage of visual perception and the statistical properties of image data to provide superior results compared with generic data compression methods which are used for other digital data. Image compression may be lossy or lossless. Lossless compression is preferred for archival purposes and often for medical imaging, technical drawings, clip art, or comics.

Lossless compression

Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates (and therefore reduced media sizes).

Related publications (27)

Temporal Conditional Coding for Dynamic Point Cloud Geometry Compression

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