Using AWS to Ingest, Store, Archive, Share and Carry out Analysis of Video Content
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22.05.18 – 56646:26Популярные
49 дней – 8526:24
Опубликовано 22 мая 2018, 18:09
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AWS London Summit 2018 - Breakout Session:
Currently customers have large volumes of CCTV data that they keep locally at remote locations. There are requirements to store this data, index and share with third parties, which can be costly and a manually intensive process. This session will walk through the use of video ingestion and storage, video frame based analysis and real-time alerting and sharing of streaming data using Amazon Kinesis Video Streams and Amazon S3. This will leverage Amazon Rekognition for image and video analysis and also discuss the architectures for analysis on edge devices such as AWS DeepLens using Amazon SageMaker and common image ML Algorithms. At the end of the session you will understand the techniques for ingesting, storing and analysing video streams using AWS ML services.
AWS London Summit 2018 - Breakout Session:
Currently customers have large volumes of CCTV data that they keep locally at remote locations. There are requirements to store this data, index and share with third parties, which can be costly and a manually intensive process. This session will walk through the use of video ingestion and storage, video frame based analysis and real-time alerting and sharing of streaming data using Amazon Kinesis Video Streams and Amazon S3. This will leverage Amazon Rekognition for image and video analysis and also discuss the architectures for analysis on edge devices such as AWS DeepLens using Amazon SageMaker and common image ML Algorithms. At the end of the session you will understand the techniques for ingesting, storing and analysing video streams using AWS ML services.
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