# VR Viewport Pose Model for Quantifying and Exploiting Frame Correlations

arXiv: https://arxiv.org/abs/2201.04060 · HTML: https://mlsanity.com/paper/2201.04060/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jan 2022.

## Built on by (most cited first, 1 of 1)

- [EyeNavGS: A 6-DoF Navigation Dataset and Record-n-Replay Software for Real-World 3DGS Scenes in VR](https://mlsanity.com/paper/2506.02380/) (2025)

## Abstract (arXiv)

The importance of the dynamics of the viewport pose, i.e., the location and the orientation of users' points of view, for virtual reality (VR) experiences calls for the development of VR viewport pose models. In this paper, informed by our experimental measurements of viewport trajectories across 3 different types of VR interfaces, we first develop a statistical model of viewport poses in VR environments. Based on the developed model, we examine the correlations between pixels in VR frames that correspond to different viewport poses, and obtain an analytical expression for the visibility similarity (ViS) of the pixels across different VR frames. We then propose a lightweight ViS-based ALG-ViS algorithm that adaptively splits VR frames into the background and the foreground, reusing the background across different frames. Our implementation of ALG-ViS in two Oculus Quest 2 rendering systems demonstrates ALG-ViS running in real time, supporting the full VR frame rate, and outperforming baselines on measures of frame quality and bandwidth consumption.