Organizations with growing security challenges are now looking to video surveillance to overcome both security and operational inefficiencies. Video content analytics software is an artificial intelligence backed technology solution that offers a broad spectrum of analytic capabilities to enhance video security systems, enabling operators to leverage existing video surveillance investments to:
By integrating video content analysis software, organizations can extend the value derived from traditional security footage and flexibly and seamlessly scale operations based on a data-driven approach.
Intelligent video analysis relies on Deep Learning and artificial intelligence technologies to drive:
This Deep Learning-driven process involves training the system to recognize and match objects, which is achieved by exposing the system to massive sets of tagged images. For instance, to teach a machine how to recognize a girl, the system must be exposed to thousands of tagged images of girls (and images without girls) so that future images of girls can be accurately identified. Of course, when trained effectively, Deep Neural Networks (DNNs) can not only distinguish based on gender, but can also recognize types of vehicles or animals and even drive activities, such as face recognition, i.e. identifying matches for specific individuals.
Once a video analytics engine processes video using these techniques, all of the extracted and identified objects are indexed as metadata so that video content can be searched; real-time alerts can be configured based on identifiable objects or behaviors; and data can be aggregated over time to generate business intelligence dashboards and reports.
Video surveillance is nearly ubiquitous, but the vast majority of the content captured is never used. The overwhelming quantities of recorded and live footage are far too vast for humans to efficiently and effectively search and review manually. Video content analytics empowers users to utilize this video without investing significant time and manpower. By making video easily searchable, actionable and quantifiable, resources can be reallocated for more critical activities, video surveillance content can be actively utilized and organizations can share video data traditionally used only for security for maximizing efficiency across business groups. Here are a few examples of how video content analytics can serve a variety of stakeholders within diverse organization types.
Like any game-changing information technology, video analytics is helping organizations do things that mere surveillance never could. From retailers to law enforcement professionals, city planners and transit agencies, and beyond, organizations are empowered to maximize existing video asset investments, transforming everyday video surveillance into actionable intelligence for security and beyond.
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