May 30, 2022, 1:12 a.m. | Haoxin Wang, BaekGyu Kim, Jiang Xie, Zhu Han

cs.CV updates on arXiv.org arxiv.org

Today very few deep learning-based mobile augmented reality (MAR)
applications are applied in mobile devices because they are significantly
energy-guzzling. In this paper, we design an edge-based energy-aware MAR system
that enables MAR devices to dynamically change their configurations, such as
CPU frequency, computation model size, and image offloading frequency based on
user preferences, camera sampling rates, and available radio resources. Our
proposed dynamic MAR configuration adaptations can minimize the per frame
energy consumption of multiple MAR clients without degrading …

arxiv augmented reality cv detection edge energy mobile reality

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