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Real-time video processing technologies continue to provide significant benefit to end users. Video Analytics have become a standard requirement in many security applications, but with the advent of artificial intelligence, video analytics uses will stretch far beyond surveillance. As we move further into 2020, surveillance cameras will be used not just for security, but also for video analytics and the metadata they produce, to obtain intelligent insights in many fields.
The introduction of complementary video intelligence technology has enabled video analytics users to derive more value from their video surveillance investments, transforming video into actionable intelligence based on deep learning techniques and artificial intelligence.
Sourcesecurity.com mentions several major trends in video analytics at the beginning of this new decade.
The key enabling technologies behind video content analysis continue to be artificial intelligence and deep learning which effectively transform live or recorded video into structured metadata that can deliver actionable and quantifiable insights.
Ongoing algorithm research and development continues to make the extraction and analysis of data increasingly efficient and accurate.
By expanding the camera coverage for real-time video processing, users can trigger alerts for broader environments and also increase data aggregation and visualization into dashboards in real-time.
Moreover, the demand for real-time information and immediacy will only grow, especially as users become more reliant on video intelligence dashboards for deriving current business intelligence.
Facial recognition against a compiled watchlist or database of digital images, either extracted from video frames or uploaded to the system is gaining momentum. This technology is posed for increased adoption, as access to ideal video and conditions to support face matching become more mainstream: As higher resolution video and more efficient processing technologies evolve, face recognition solutions are becoming more effective and accurate.
Accurate video analytics – the increasing availability of high-resolution video (4k, 8k) is enabling more sophisticated and accurate video analytics. Higher resolution video makes it possible to more accurately analyse and identify objects in crowds, for triggering real-time rule-based alerts when certain conditions are met, searching and filtering video, etc.
Technological advances drive precise analytic capabilities, such as face recognition and count-based alerting. However, the steep hardware requirements to support heavier video processing remain a barrier, according to a Briefcam evaluation. As long as the cost of hardware is high, mass market adoption of higher resolution cameras will be somewhat stilted, but it’s definitely an evolution we’ll continue to monitor in the coming years.
Cloud-based video analytics is another trend that is expected to have more widespread use, as cloud implementations offer ease of deployment and a low cost of entry. With advances to cloud development, in general, cloud platforms now boast robust cyber security, as well.
At the very least, the migration to cloud platforms will offer end users the freedom of choice when it comes to video content analytics deployment, whether the cloud, on-premises or hybrid of the two is most suited to maximise their existing video surveillance networks.
The video analytics field is posed for continued evolution in 2020, because of rapid enabling hardware and software progress that is making the technology more accessible and more valuable.