Video analytics for sensitive places

Protecting areas of interest and streamlining access with Augmented Vision

Today there is an immense amount of videos and images due to the prevalence of CCTV streams, smartphones and more. Augmented Vision is a video analytics solution which helps survey and protect buildings, infrastructure and areas of interest by making sense of all available data, while protecting citizens’ and consumers’ privacy with the highest level of data protection.

It can be used to prevent security incidents in highly frequented public or private spaces, but also to ensure frictionless access to restricted areas.

Thanks to its powerful algorithms, it can also interpret and tag hours and days of CCTV streams and thousands of photos to help find subjects and objects of interest in post-event investigations.

This powerful video analytics solution can be set up for three main applications:

Boost the efficiency of operators to find leads in a faster and more automated way,
Provide actionable intelligence and help monitor video flow and alerts security staff on the appearance of persons of interest,
Allow secure and frictionless access to authorized personnel: by detecting and identifying multiple persons approaching an access point, it brings a powerful layer on top of existing video and access control systems.

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Easy to implement

This video analytics solution uses everyday off-the-shelf hardware, including IP cameras, networks, servers, and where possible, existing infrastructure.
Easy to integrate

Using Open API standards, solution providers can easily integrate Augmented Vision with other systems that manage CCTV videos, customer relationships and security, including access control.
Save time

Augmented Vision automatically extracts videos and images and classifies the content, turning it into searchable actionable intelligence.

500 hours

of video footage with half a million faces analyzed in almost a day, on a small workstation

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Downloads & Softwares

Augmented Vision platform brochure

.pdf (1.80 MB)