Compression of Uniformly Distributed Unit Quaternions
arXiv cs.GR presents a new method for compressing uniformly distributed unit quaternions, the rotation representation that shows up everywhere from animation to rendering. The paper is aimed squarely at the practical problem developers keep running into: rotation data is compact in theory, but at scale it still eats memory and bandwidth.
The authors compare several quaternion parameterizations across error behavior, quantization, compute cost, and storage efficiency. Their main result is an infinity-norm parameterization paired with an optimized warp function, which they say consistently produces the smallest maximum error while also offering the best storage efficiency. Decompression cost is reported as equal to or lower than the methods commonly used today.
That matters for teams shipping animation-heavy or data-heavy graphics features. The paper demonstrates the approach in tangent-space normal mapping, skeletal animation with blend weights, and Gaussian splatting, suggesting the technique could be useful anywhere rotation payloads are replicated, streamed, or packed into tight GPU budgets.
For engine and tools developers, the interesting part is the tradeoff profile: lower worst-case error without paying extra on decode. If the method holds up in production code, it could be a straightforward win for asset pipelines that need to squeeze more out of memory, cache, and bandwidth.
“smallest maximum error and the best storage efficiency”
- what
- A paper proposes a new compression method for uniformly distributed unit quaternions.
- who
- Carsten Faber, Bastian Kuth, Rinaldo Schuster, Daniel Pauls, and Quirin Meyer.
- when
- Submitted to arXiv on 15 Oct 2026.
- impact
- Could reduce memory use and bandwidth for rotation data in rendering and animation pipelines.
Promising compression gains with low decode cost
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