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ILCAS: Imitation Learning-Based Configuration-Adaptive Streaming for Live Video Analytics with Cross-Camera Collaboration. (arXiv:2308.10068v2 [cs.NI] UPDATED)
cs.LG updates on arXiv.org arxiv.org
The high-accuracy and resource-intensive deep neural networks (DNNs) have
been widely adopted by live video analytics (VA), where camera videos are
streamed over the network to resource-rich edge/cloud servers for DNN
inference. Common video encoding configurations (e.g., resolution and frame
rate) have been identified with significant impacts on striking the balance
between bandwidth consumption and inference accuracy and therefore their
adaption scheme has been a focus of optimization. However, previous
profiling-based solutions suffer from high profiling cost, while existing deep …
accuracy analytics arxiv cloud collaboration dnn edge encoding imitation learning inference network networks neural networks rate servers streaming video video analytics videos