Let AI increase productivities and save Cost, AI Video Surveillance Video Analytics Facial Recognition Artificial Intelligence Best Value Contactless from COVID Virus Smart Identifying VIP Blacklist.
While video surveillance analytics has been promoted, hyped and lamented for nearly 20 years, next year, 2020, will be the year that it finally goes mainstream, marking a major advance for the industry and security users.
Why This Is Important
Alerting and searching is made much harder when systems cannot determine what is a person vs what is leaves, shadows, headlights, birds, etc. Alerting cannot be trusted since so many of the alerts will be obviously false and searching is more difficult since users are forced to wade through so many clearly irrelevant results.
This will solve a long-standing frustration of surveillance systems – that there is so much video but no way to manually ‘look’ at it all. Instead of doing so, AI will automate that process, making systems significantly more valuable and increasing demand for systems.
What Will Go Mainstream – People, Then Vehicles
“AI” is an immense field. To be specific, what we are confident will go mainstream in 2020 is the ability to reliably detect what is a person vs what is not. Vehicle detection will follow.
Harder Not Mainstream
Harder analytics, like facial recognition, tracking people across cameras, detecting smaller objects (like guns, knives, backpacks, etc.) will not be mainstream in 2020. There will certainly still be many areas where companies can differentiate on harder “AI”.
Mainstream Means Widely Offered
Obviously, some companies have offered “AI” / video analytics that have worked for years, however, this has remained a distinct niche. For example, see the (mostly) terrible results from our 2018 professional video analytic shootout.
The difference in 2020 is that it is going mainstream, meaning that almost all manufacturers will be offering fairly accurate and reliable people detection analytics. And the ones that do not are going to stand out as outliers, the other way.
20 Years In the Making, Nearly
What is wild about this is that for nearly 20 years, companies have been claiming to deliver working video analytics. For example, it has been more than 16 years since Object Video’s analytics won ‘Best In Show’ (one of a series of ‘best’ failures).
Video analytics has been hyped for so long that that 15 years ago, most industry professionals viewed analytics as being more promising than IP cameras. Of course, the last decade has shown otherwise, with IP / MP surging and analytics dealing with a decade of despair.
Why 2020 Is Different
This time really is different, due to (1) deep learning and (2) it being productized in hardware and software kits that make it easy for this to go mainstream.
The benefit of deep learning is that, in the past, video analytics relied on heuristics (like what is the aspect ratio of the pixels changing and how long has it lasted, etc.). These heuristics were often, literally, shots in the dark and were prone to major errors. With deep learning, systems are trained with examples of what is a person (e.g.) and what is not.
The downside of deep learning is that historically it has been very resource-intensive (think servers filled with GPUs).
What is making deep learning go mainstream for AI video analytics is that it is being productized to fit with video surveillance cameras and recorders. On the hardware side, there is Intel Myriad (Movidius), Ambarella CV chips, Huawei Hisilicon, Qualcom and others providing the chips that make it much turn key to deliver AI on these devices. On the software side, the most notable is XNOR.ai, the inventors of YOLO, who have built a business providing optimized software modules to work even on commodity hardware. Read more….
AI Video Surveillance Video Analytics Facial Recognition Artificial Intelligence Best Value Contactless from COVID Virus Smart Identify VIP Blacklist
- AI Video Surveillance: Traditional video surveillance systems require human operators to monitor live feeds or review recorded footage. AI-powered video surveillance systems can analyze video streams in real-time, automatically detecting and alerting security personnel to suspicious activities or potential threats. This technology significantly increases productivity by reducing the need for manual monitoring and allows security personnel to focus on critical situations.
- Video Analytics: AI-based video analytics can extract valuable insights from surveillance footage. For example, it can count the number of people in a crowd, track movement patterns, identify objects or vehicles, and even detect anomalies such as abandoned bags or unauthorized access. By automating these processes, businesses can save costs on manual monitoring and improve security efficiency.
- Facial Recognition: Facial recognition technology utilizes AI algorithms to analyze and identify individuals based on their unique facial features. It can be integrated into surveillance systems to automatically identify known individuals or match faces against a database of VIPs or blacklisted individuals. This streamlines security processes, enhances access control systems, and saves costs by reducing the need for manual identification checks.
- Contactless Identification: With the ongoing concerns around COVID-19, contactless identification has become crucial in minimizing physical interactions. AI-powered systems can use facial recognition or other biometric data to identify individuals without requiring physical contact, such as fingerprint scanning or ID card swiping. This technology not only increases productivity by reducing wait times but also promotes safety by minimizing the risk of virus transmission.
- Smart VIP and Blacklist Identification: AI can automate the identification of VIPs and blacklisted individuals in real-time. By integrating facial recognition with existing databases, AI systems can quickly identify VIPs and provide personalized services, enhancing customer satisfaction. Simultaneously, the system can identify blacklisted individuals and send alerts, enabling security personnel to take immediate action, thereby improving safety and reducing potential costs associated with security breaches.
Overall, AI-driven solutions in video surveillance, facial recognition, and contactless identification offer numerous benefits, including increased productivity, enhanced security, reduced costs, and improved safety measures, particularly in the context of COVID-19.