用于视频监控的低功耗计算机视觉引擎

2018 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA) Pub Date : 2018-11-01 DOI:10.1109/CICTA.2018.8705947

Ke Xu, Yu Li, Bin Han, Xiao Zhang, Xin Liu, Jisong Ai

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引用次数: 1

摘要

本文介绍了用于实时视频分析的计算机视觉引擎(CVE)的设计和VLSI实现。它为各种视觉任务(如人脸检测，物体检测，运动跟踪等)的耗电计算卸载CPU/GPU。该设计具有22个计算内核，并分为三个主要类别。该CVE集成在智能视频监控SoC(片上系统)中，并采用台积电28纳米技术制造。总硬件成本为392K门和75.5 KB内存。实测结果表明，在400MHz工作频率下，该设计能够实现$1920\times1080$ 30fps的实时视频分析。总功耗为20mW，能效为0.32nJ/像素。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Low-power Computer Vision Engine for Video Surveillance

this paper presents the design and VLSI implementation of a CVE (Computer Vision Engine) for real-time video analysis. It offloads CPU/GPU for the power-hungry computation for various vision tasks such as face detection, object detection, motion tracking, etc. The design features 22 computation kernels and is divided into three main categories. The proposed CVE is integrated in a smart video surveillance SoC (System on Chip) and fabricated with TSMC 28nm technology. The total hardware costs are 392K gates and 75.5 KB memory. The measured results show that the design is able to achieve $1920\times1080$ 30fps real-time video analysis when running at 400MHz. The total power consumption is 20mW and 0.32nJ/pixel of energy efficiency.

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来源期刊

2018 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)

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