RemoteVIO: Offloading Head Tracking in an End-to-End XR System

Power consumption, and the resulting limitation to computational load, is a first-order constraint in designing comfortable all-day-wear extended reality (XR) devices that can provide rich immersive experiences. This paper concerns reducing XR device power consumption by offloading head tracking, one of the top CPU and power consumers, to a remote server. We present RemoteVIO, the first open-source end-to-end XR system that offloads head tracking (visual inertial odometry or VIO) to a remote server. Our work distinguishes itself from past studies on computation offloading in XR by properly addressing two under-explored but critical aspects: 1) a comprehensive evaluation of user experience in a complete end-to-end XR system and 2) a quantification of the net power savings on real hardware.

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Publication Details

Published
2025-03-26
DOI
https://doi.org/10.1145/3712676.3714442
Citations
8
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
11.90

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article

RemoteVIO: Offloading Head Tracking in an End-to-End XR System

Javier Ramirez-Perez, William Sentosa, Qinjun Jiang, Yihan Pang et al.
8 citations
IoT and Edge/Fog Computing
11.90
article

RemoteVIO: Offloading Head Tracking in an End-to-End XR System

Javier Ramirez-Perez, William Sentosa, Qinjun Jiang, Yihan Pang, J. Zhang, Dibakar Das, D. Gonzalez-Aguirre, P. Brighten Godfrey, Muhammad Huzaifa, Sarita V. Adve, Shunji Gao
article en
8 citations

Abstract

Power consumption, and the resulting limitation to computational load, is a first-order constraint in designing comfortable all-day-wear extended reality (XR) devices that can provide rich immersive experiences. This paper concerns reducing XR device power consumption by offloading head tracking, one of the top CPU and power consumers, to a remote server. We present RemoteVIO, the first open-source end-to-end XR system that offloads head tracking (visual inertial odometry or VIO) to a remote server. Our work distinguishes itself from past studies on computation offloading in XR by properly addressing two under-explored but critical aspects: 1) a comprehensive evaluation of user experience in a complete end-to-end XR system and 2) a quantification of the net power savings on real hardware.

Intel (United States) (US), University of Illinois Urbana-Champaign (US), Broadcom (United States) (US)
National Science Foundation, Cisco Systems
Affordable and clean energy
Openalex Percentile: Top 2%
IoT and Edge/Fog Computing
11.90
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