PETRI: Reducing Bandwidth Requirement in Smart Surveillance by Edge-Cloud Collaborative Adaptive Frame Clustering and Pipelined Bidirectional Tracking

Neural networks running on cloud servers have been widely used in smart surveillance, but they require high bandwidth to upload videos. Edge-cloud collaborative encoding based on ROI (Region-Of-Interest) can reduce bandwidth requirement, but it suffers from inaccurate ROI detection due to feedback l...

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Bibliographic Details

Published in:	2021 58th ACM/IEEE Design Automation Conference (DAC) pp. 421 - 426
Main Authors:	Liu, Ruoyang, Zhang, Lu, Wang, Jingyu, Yang, Huazhong, Liu, Yongpan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 05.12.2021
Subjects:	Bandwidth Collaboration collaborative architecture edge computing Image edge detection Object detection Pipelines Surveillance Target tracking
Online Access:	Get full text
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