Deep Learning-Driven Video Analytics
Video analytics is a technology that leverages existing video surveillance networks to derive searchable, actionable, and quantifiable intelligence from live or recorded video content. Driven by artificial intelligence and deep learning, video intelligence software detects and extracts objects in video, identifies each object based on trained Deep Neural Networks, and then classifies each object to enable intelligent video analysis, including search and filtering, alerting, and data aggregation and visualization.
BriefCam’s Video Content Analytics Platform processes raw video to:
Understand the context of the entire scene and its background
Create a structured database of information out of the unstructured video data
Empower users with granular search, smart alerting, and comprehensive reporting
How Does Video Analytics Work?
What critical intelligence can a video analytics solution derive from a video segment? We’ll explain using these two videos. In the first video, you can see a woman riding a bicycle. Based on machine learning techniques, video analytics software would identify a person and classify her as a woman. It would derive the color of her clothing, the bicycle she is riding, as well as its speed and direction.
While the human eye could quickly and easily isolate the data in the first video, it would be difficult to do the same on a more complex scene, such as the second video. Organizations today record overwhelming amounts of video that human operators could never effectively, efficiently and comprehensively understand without intelligent video analytics to accelerate the process.
BriefCam harnesses advanced GPUs to analyze more video, deliver actionable insights faster, and extract richer metadata.
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Why Use Video Analytics?
Traditionally, video surveillance cameras have been used primarily by physical security and law enforcement teams to drive investigations and improve real-time response to situations. However, in recent years organizations have discovered that they can get much more value from their video surveillance networks by complementing them with video analytics systems. As a result, video analytics are now used not only by physical security and law enforcement professionals, but by a variety of operators, from Marketing to Operations, Facility Management, Customer Experience teams and more – across a diverse array of organizations and industries.
Download this eBook to learn the WHAT, WHO, WHY, and HOW of video analytics
Why is Video Analysis Important?
Diverse organizations traditionally rely on video surveillance for security purposes. By maximizing these existing investments with video analytics, various business units can leverage video intelligence in new and impactful ways.
From accelerating post-event investigations and proactively responding to security incidents as they unfold, to deriving visitor demographic profiles, behavioral patterns and operational inefficiencies, such as crowds and queues that can be avoided with real-time intervention, video analytics provides the breadth of intelligence needed to bolster security, customer experiences, business operations and – ultimately – revenues.
