Transparent AR Processing Acceleration at the Edge

Proceedings of the 2nd International Workshop on Edge Systems, Analytics and Networking(2019)

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摘要
Mobile devices are increasingly capable of supporting advanced functionalities but still face fundamental resource limitations. While the development of custom accelerators for compute-intensive functions is progressing, precious battery life and quality vs. latency trade-offs are limiting the potential of applications relying on processing real-time, computational-intensive functions, such as Augmented Reality. Transparent network support for on-the-fly media processing at the edge can significantly extend the capabilities of mobile devices without the need for API changes. In this paper we introduce NEAR, a framework for transparent live video processing and augmentation at the network edge, along with its architecture and preliminary performance evaluation in an object detection use case.
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关键词
Edge Computing, Machine Learning
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