Live Video Analytics with Microsoft Rocket for reducing edge compute costs

Ganesh Ananthanarayanan,Yuanchao Shu, Mustafa Kasap, Avi Kewalramani, Milan Gada,Victor Bahl

user-60ab1d9b4c775e04970067d6(2020)

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摘要
Microsoft Rocket, an open-source project from Microsoft Research, provides cascaded video pipelines that combined with Live Video Analytics from Azure Media Services, makes it easy and affordable for developers to build video analytics applications in their IoT solutions. Unprecedented advances in computer vision and machine learning have opened opportunities for video analytics applications that are of wide-spread interest to society, science, and business. While computer vision models have become more accurate and capable, they are also becoming resource-hungry and expensive for 24/7 analysis of video. As a result, live video analytics across multiple cameras also means a large computational footprint on premises built with a good amount of expensive edge compute hardware (CPU, GPU etc.). Total cost of ownership (TCO) for video analytics is an important consideration and pain point for our customers. With that in mind, we integrated Live Video Analytics from Azure Media Services and Microsoft Rocket (from Microsoft Research) to enable an order-of-magnitude improvement in throughput per edge core (frame per second analyzed per CPU/GPU core), while maintaining the accuracy of the video analytics insights.
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关键词
Analytics,Frame rate,Total cost of ownership,Multimedia,Enhanced Data Rates for GSM Evolution,Computer science,Throughput (business),Point (typography),Footprint,Rocket (weapon)
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