How Video Analytics is Changing the Way We Store Video

Presented by

Kevin Cone, Intel; Glyn Bowden, HPE; Jim Fister, The Decision Place

About this talk

There is a new wave of cognitive services based on video and image analytics, leveraging the latest in machine learning and deep learning. In this webcast, we will look at some of the benefits and factors driving this adoption, as well as explore compelling projects and required components for a successful video-based cognitive service. This includes some great work in the open source community to provide methods and frameworks, some standards that are being worked on to unify the ecosystem and allow interoperability with models and architectures. Finally, we’ll cover the data required to train such models, the data source and how it needs to be treated. However, there are challenges in how we do this. Many archives were analog and tape based which doesn’t stand up well to mass ingestion or the back and forth of training algorithms. How can we start to define new architectures and leverage the right medium to make our archives accessible whilst still focusing on performance at the point of capture? We will discuss: •New and interesting use cases driving adoption of video analytics as a cognitive service •Work in the open source arena on new frameworks and standards •Modernizing archives to enable training and refinement at will •Security and governance where personal identifiable information and privacy become a concern •Plugging into the rest of the ecosystem to build rich, video centric experiences for operations staff and consumers After you watch the video, check-out the Q&A blog:
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SNIA is a not-for-profit global organization made up of corporations, universities, startups, and individuals. The members collaborate to develop and promote vendor-neutral architectures, standards, and education for management, movement, and security for technologies related to handling and optimizing data. SNIA focuses on the transport, storage, acceleration, format, protection, and optimization of infrastructure for data.