Overview

 

Real-Time video Analytics Engine is a Platform that utilizes advanced image processing algorithms to turn video into actionable intelligence. Large Scale Video Processing is the greatest challenge holding a great potential for Analytics. Real-Time Video Analytics can be used for Monitoring Traffic Control, Retail Store Monitoring, Surveillance and Security. 

 

XenonStack's Real-Time Video Analytics Platform is real-time, low cost, accurate analysis of live videos using Open Source Big Data Technologies including OpenCV, Apache Kafka, Apache Spark, HDFS, Tensor Flow, and Amazon S3. 

 

 

Business Challenge

 

  • Traditional Computer Vision System suffers from a limitation, that a server along with CV library collects and process the data at the same time. A failure in the server  causes loss of Streaming Video Data.

  • Detecting a node failure and switching the processing to another node may result in fragmentation of data.

  • Major challenge relies on running an image processing algorithms in a dynamic environment.

 

Thus managing and efficiently analysing this data brings us with a challenge to build a system which can eliminate the addressed problems.

 

Solution Offered

 

XenonStack Team came up with a solution to perform real-time video analytics backed by open source big data technologies.

 

The system is divided into three main components -

 

  • Video stream collector

  • Stream data buffer

  • Video stream processor

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Industry

General


Technologies

Apache Spark, Apache Kafka, OpenCV, Amazon S3, HDFS, Apache Zookeeper, Tensor Flow

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