Articles by Alan Ataev
ISC West, the world's largest security industry trade show, is just around the corner. This in-person show gathered more than 1,000 manufacturers and over 30,000 visitors from all over the world in 2019. On top of that, more than 200 brands exhibited at ISC West for the first time. This year's event promises to be just as exciting, if not more so. Let’s overview some leading security trends in video management systems development, and what's worth your time and attention at ISC West 2020. AI analytics Emerging two or three years ago, the AI-based video analytics market is experiencing a boom in growth. The prototypes and ideas displayed at ISC West 2019 could This year's event promises to be just as exciting, if not more soalready be part of a functioning system today. There's a lot of hype around this new trend. So, if you're looking for solutions for your needs, it is important to be able to tell the difference between technologies that work and marketing bluster. To do that, you have to understand what today's AI-based analytics (also often referred to as a neural network, deep learning, or machine learning) can and can't do. Let's start with what AI can't do in video surveillance. It can't analyse the sequence in which events occur or understand the 'logic' of what's happening in the scene. In other words, there's no such thing as a 'suspicious behavior detection tool'. Nevertheless, neural networks are really good at recognising and classifying objects. For instance, they can distinguish humans from vehicles, vehicles from other moving objects, and cyclists from pedestrians. Neural network trackers This technology is primarily used as a neural network tracker or object tracker that can identify and track objects of a specific type. Usually, it's applied to complex scenes with a large amount of non-relevant details where a classic tracker would drown in false alarms. The neural tracker can be used to detect people in dangerous areas at production facilities, cyclists riding on pedestrian lanes, or poachers trying to sneak into a nature preserve. Neural networks are really good at recognising and classifying objectsObject identification function can be used for other site-specific tasks, such as detecting people without a helmet or a high-visibility vest at facilities where those are required by safety regulations. It can also be used to detect fire and smoke in open spaces, or at big premises with high ceilings or active air circulation, where common fire alarm systems can't be used or may go off too late. Behaviour analytics Behavior analytics is another field of analytics based on artificial neural networks. Even if recognising suspicious or inappropriate behavior is nearly impossible, it can detect risky situations based on human postures, such as an active shooter pose, raised arms, crouching, or man down. In addition to that, AI has been successfully used to perform facial and number plate recognition for quite some time now. Although these systems aren't new, their recognition quality improves each year. Looking for solutions? You'll definitely find some interesting and new options from developers specialising in VMS and modular AI analytics at ISC West 2020. Even if recognising suspicious or inappropriate behavior is nearly impossible, AI can detect risky situations based on human postures Smart search The ability to perform a quick, flexible search in a video archive is one of the most important features of a video surveillance system. In many ways, it's even more AI has been successfully used to perform facial and number plate recognition for quite some time nowimportant than real-time monitoring itself. Constantly keeping an eye out for what's happening onsite is the security service's job. Medium- to large-sized companies usually have that kind of department. Meanwhile, lots of small businesses and households use video footage to investigate accidents, resolve conflicts, or analyse employee's work. They generally don't need real-time monitoring, but video search is a crucial element. The most basic search tools offer an interface that enables easy access to recorded video and event-based search (from video analytics, detectors, etc.). Smart systems with forensic search features that allow the user to set criteria enhance the system's search capabilities even more. How it works VMS analyses the video as it is recorded and saves the resulting metadata to a database. In the most basic case, the metadata contains information about motion in the scene as well as the moving object's coordinates. When searching, you can select an area of interest within the frame and take a quick look at all video segments containing motion in this area. More advanced systems save the parameters of moving objects, such as their size, color, motion speed and direction. TThe ability to perform a quick, flexible search in a video archive is one of the most important features of a video surveillance systemYou'll quickly find what you're looking for by setting more precise criteria. The first VMS with forensic search features appeared in the early 2010s. Since then, a growing number of users and VMS developers have recognised the importance of these tools. More and more manufacturers enrich their products with forensic search features, starting from basic search by motion detection. Integrating search functions with AI Recently, search technologies have gone even further by integrating search functions with AI analytics. Some systems are capable to recognise all faces and number plates captured by cameras and save them to the database. You can quickly find all videos containing an image of a person or a car just by searching a photo or a number plate across multiple camera archives at a time. One usage scenario for these systems can be seen in law enforcement deploying them to find suspects using CCTV cameras around the city. Another option for integrating smart search and AI is searching by criteria based on a neural network tracker. When you use it, you can set object's size, color, motion speed and direction in the scene, as well as object's type (such as a human or a vehicle). So, if you need to find out when a red car appeared in the surveillance area, the system will show you only red cars while ignoring other objects like people in red clothes. This technology lets you find what you're looking for even faster. If you or your clients use VMS primarily to record video, be sure to ask the manufacturers you'll talk to at the show what search capabilities they offer. More advanced systems save the parameters of moving objects, such as their size, color, motion speed and direction Hardware AI acceleration High CPU resource consumption is one of the hardest challenges that stem from implementing a neural network–based video analytics system. This significantly decreases the number of cameras that can be connected to a server that hosts AI analytics. It also makes the system much more expensive. AI technology lets you find what you're looking for even fasterThe solution is to use AI accelerators. GPUs and dedicated accelerator cards are used on servers to provide hardware acceleration for the neural networks' workload. These devices are mostly manufactured by Intel and NVIDIA. Intel also offers the OpenVINO™ toolkit, a software package for developers that helps distribute workload between CPU, GPU, and accelerators as effectively as possible using all available resources. New solutions Due to AI's growing popularity, lots of minor microchip manufacturers became interested in developing neural accelerator chips. The healthy competition will work in the market's favor, serving to stimulate tech development and cut prices. New solutions in the field were on display at ISC West 2019; they'll definitely be present at ISC West again in 2020. Developers specialising in VMS and modular AI video analytics should absolutely check these out. But users should understand that it's impossible to build a cost-effective video surveillance system with significant number (10–20 and more) of AI analytics channels without using neural accelerators. That said, various accelerator models may significantly differ in price and power consumption. So, when you talk to developers specialising in VMS and AI analytics modules, ask what accelerator makes and models they support. In conclusion Whether you're an integrator looking for interesting VMS offers for clients or an end-user searching for solutions to your own tasks, check out what AI analytics can do. This sector is developing very fast and is continuously introducing new features that may be just what you're looking for. Incorporating forensic search in recorded video footage is key to building an effective video surveillance system for users, and important to creating a unique product offering for integrators. Needless to say, you can't build a cost-effective video surveillance system without using CPU resources wisely. If a system's functionality completely aligns with what you're looking for, ask what neural accelerator hardware it supports to correctly estimate the cost of your video servers.
Video surveillance is commonly associated with security. But in most cases, it's used to record incidents and assist in investigations after the fact rather than prevent undesirable events. Artificial intelligence–powered video analytics is a highly promising trend that fundamentally changes the way things work. Extracting manageable data from a video stream can help recognise risky situations early on, minimising damage and, ideally, completely avoid emergencies. At the same time, AI significantly expands the areas of application of video surveillance beyond security systems. AI significantly expands the areas of application of video surveillance beyond security systems However, the hype around this new, trendy technology prevents the potential user from choosing quality solutions in a wide variety of products. This often leads to over-expectation, followed by a complete let-down. Can AI-powered video analytics really be the key to a technological breakthrough in video surveillance? We'll take a look at what the technology can do, what it can't, and where it can go from here. Technological breakthrough or just another bubble? It's often said that the video management software (VMS) market is becoming increasingly commoditised and widely available. A lot of products with similar features (or, at least, similar promises from the manufacturer) make it hard to choose. As a result, vendor names and reputations are turning into one of their primary selling points. Manufacturers have two choices available: get wrapped up in a price war and rely on cutting expenses, or offer a product that's truly innovative and revolutionary. Manufacturers have two choices available: get wrapped up in a price war, or offer a product that's truly innovative and revolutionary VMS developers who choose the second route are gravitating towards creating products that use artificial intelligence based on neural networks and deep learning. Emerging two or three years ago, the AI video analytics market is experiencing a boom in growth. This new tech wave has stirred the still, stagnant backwaters of the VMS world and gave small, ambitious developers something to be optimistic about. It seems they now have a chance to emerge as market leaders in the next few years. However, the hype around this popular trend is raising reasonable concerns among experienced security industry professionals. These concerns come from clients looking for a solution to their problems, and from suppliers building a long-term development strategy. This largely resembles another tech bubble, like the one built up around pre-AI video analytics and burst when it became clear that the promises around it were pure marketing hype. However, there are factors that indicate that AI-powered video surveillance systems aren't another bubble. The three factors The first — and the main one — comes from systems already in place on customers' sites. They fulfill the same promises made during the previous bubble by hotheads in a rush to teach the computer to analyse events in real time using a classical algorithmic approach. The second is the fact that this new technology has seen investment from not only software and cloud startups, but also established VMS developers. Even giants like Intel, which has presented a full line of neural network accelerator hardware and a set of software tools that streamlines working with them, specifically in the field of computer vision. This new technology has seen investment from not only software and cloud startups, but also established VMS developers The third factor lies in artificial intelligence's abilities. AI plays chess, drives cars, and works wonders in many other fields. Why shouldn't it be applied to video monitoring and analysis? What AI can do Just what can artificial intelligence do in video surveillance systems at this stage of development? It can't quite analyse a sequence of events and understand the "logic" of what's happening in the cameras' field of view. At least not yet. But it's probable that AI will learn to do this in the next few years. But neural network analytics can already detect, classify, and track objects very well, providing high accuracy even in busy scenes. Artificial intelligence can be used in the real world to: Detect smoke and flames for early fire warning at open areas (forest, open warehouse, parking lot, etc.) Distinguish people/vehicles from animals and other moving objects, e.g. to protect the perimeter of a nature park from poachers Distinguish a person in a helmet and protective clothing from a person without them to prevent accidents at a dangerous production facility or construction site Count objects of a specific type, e.g. cars in a parking lot, people in the sales floor, wares moving on a conveyor belt, etc. in non-security-related solutions Those are just a few examples. After training a neural network, it can tackle other, similar tasks, too. Generally, a neural network trained in specific conditions isn't replicable. In other words, it won't work as well under different conditions. On the other hand, developers have learned how to quickly train AI for the needs of a specific project. The most important requirement is having enough video footage. Somewhat apart from that is the use of neural networks in facial and automatic number-plate recognition. This is an example of reproducible neural networks (train once, deploy everywhere), which makes them more appealing commercially. If non-reproducible neural networks have only recently become economically feasible due to the rapid evolution of specialised hardware (aforementioned Intel's product, for example), then the use of AI in facial recognition and ANPR has been well established for a long time. The use of AI in facial recognition and ANPR has been well established for a long time Another kind of AI analytics that we'll explore is behaviour analytics. This function, probably more than any other, is bringing video surveillance systems closer to understanding what's happening on camera. Its potential is vast. How behaviour analytics works From a technical point of view, behaviour analytics combines artificial intelligence with a classic algorithmic approach. A neural network trained on a multitude of scenarios can determine the position of the bodies, heads, and limbs of humans in the camera's field of view. The algorithm outputs an array of data containing descriptions of their poses. Conditions can be set for data to detect a specific pose, such as raised hands, prostrated or crouching persons. Developers can use this to quickly create new detection tools to identify potentially dangerous behavior specified by a government or business client. There's no need for additional training of the neural network. How behaviour analytics can be deployed Someone crouched down next to an ATM could be a technician, CIT guard, or burglar. Bank security should be notified in any of the cases. A person in shooter position, together with a bank employee or cashier with their hands raised could indicate a robbery. The system can be configured to automatically send alerts with a surveillance snapshot to the police so they can assess the threat and take action if needed. It's vital that the police receive the alert, even if the employee is unable to activate the alarm. In many cases, attention should be directed to a prostrate individual. This could be somebody who needs immediate help, or it could be someone sleeping in an inappropriate public place, for example, a 24/7 ATM space. Behavioural analytics can also be used to ensure workplace safety. For example, tracking whether employees are holding the handrails when using the stairs at a manufacturing facility or a construction site. What now? Behaviour analytics can be deployed wherever your clients' imagination takes them. With this feature, practically any pose that indicates potentially dangerous behaviour can be detected. Timely response to an alarm helps avoid material damages or, in other situations, casualties. Practically any pose that indicates potentially dangerous behaviour can be detected An area of potential development for behaviour analytics is the ability to analyse a sequence of poses by the same person or a combination of poses and relative positions of several individuals. That will be the next level of evolution in AI's use in video surveillance: moving from "detecting" to "understanding" behaviour in real time. In its most basic form, this type of analytics can be deployed to detect deviations from the search procedure in correctional facilities when a person being inspected must assume a pre-defined sequence of poses. A more advanced form allows it to detect any kind of abnormal behaviour, such as a brawl breaking out in a public space. Ideally, behaviour analytics can predict dangerous situations based on nearly imperceptible cues gleaned from collected statistics and a Big Data analysis. At the moment, this sounds like pure fantasy, but what seemed like whimsy not too long ago is now a reality with AI. It's already beaten humans in chess and the game of Go (Weiqi). Will artificial intelligence be able to outplay humans at charades one day? It's entirely possible that we'll soon see for ourselves.
Dahua Technology, a solution provider in the global video surveillance industry, advocates openness and believes that an industry ecosystem can benefit all industry players. At Security Essen 2018, it launches the Dahua Integration Partner Program (DIPP), aiming to extend collaboration with 3rd party partners in technology integration and business development DIPP focuses on creating comprehensive and integrated solutions with 3rd party partners for wider customer and end-user base. Featuring three partner levels - Strategic Partner, Golden Partner and Silver Partner - DIPP ensures that its partners enjoy multiple benefits through Dahua Technology’s global network. Dedicated marketing support Partners who specialise in Video Management Software, Access Control System, Video Analytics, Physical Security Information Management, Alarm Systems, Cloud-based Services and Other Vertical Systems that involve Security Surveillance are most welcome to join the program. DIPP benefits partners on both technical and business sides, including in-depth marketing, project and technical support. Marketing-wise, DIPP partners enjoy dedicated marketing support including co-marketing opportunities at Dahua Technology’s global events, recommendation in Dahua 3rd-party-partner-solution catalog, etc. Dahua Technology guarantees feedback within 24h, dedicated technical support, opportunities for sample borrowing Technical-wise, Dahua Technology guarantees feedback within 24h, dedicated technical support, opportunities for sample borrowing, roadmap sharing & product introduction, and free training regarding Dahua Technology integration protocols. The key is that Dahua Technology ensures considerable benefits at Project part, including end-to-end support, opportunities for projects pipelines sharing and product recommendation, etc. Win-win results So far, some 3rd party partners have joined DIPP, like Ivideon, AxxonSoft, to name just a few. “We’re happy to launch DIPP, a program aiming to better serve our partners and achieve win-win results.” said James Wang, Deputy General Manager of overseas business at Dahua Technology. “We were the first to implement a solution on Dahua Open Platform, and we're very happy to be among the first companies to participate in the Dahua Integration Partner Program. Dahua Technology's innovative technologies, particularly its development of deep-learning video analytics, completely aligns with our vision of how video surveillance should develop. I'm confident that, together, we will create products that grow our value proposition for both our partners and clients.” Said Alan Ataev, Global Sales Director at AxxonSoft.
Dahua, a video surveillance solution provider, has announced another breakthrough giving integrators, resellers and users unprecedented levels of access to its newly launched DHOP (Dahua Open Platform), which allows third-party applications to be downloaded and installed on Dahua network cameras (currently only available on the Ultra series IP cameras but, in the future, will be available on all new models). Third-party application management DHOP is user-friendly in several ways. For third-party partners, it eliminates some of the previous restrictions from Dahua, allowing them to develop their own applications. They can also develop their own webpage/web clients to manage their applications. For integrators, resellers and end users, it provides them with choices for the most suitable add-on applications developed by third-party partners, which have been comprehensively tested and verified by Dahua, thus their interoperability and reliability have been guaranteed. Cooperation with Dahua through DHOP will bring wider benefits in the long-term. Strong support is guaranteed not only during development but also during the later stages. Verified and tested applications will be released on Dahua’s website, boasting access to a global user base. DHOP partners have the potential to participate in various marketing activities and be promoted via the Dahua global partner networks. End users can purchase licenses directly from DHOP partners, for whom Dahua will help to release the license in cameras. Facilitated video analytics AxxonSoft Ltd. was the first one to develop a solution based on the Dahua Open Platform. An application installed on the camera collects information about moving objects in the frame, including coordinates, direction of movement, size, speed, color, and so on. This metadata is transmitted to the Axxon Next VMS server along with the video stream. The data is then: Used for powerful scene analytics in the Axxon Next VMS. Saved in the archive for instant criteria-based video search. The joint solution by Dahua Technology and AxxonSoft has multiple advantages over systems with server-side video analytics, since it allows the server to process about 10 times more video feeds, and passing raw metadata (instead of events) makes the system very flexible. Users are not limited to the detection tools available on a camera, since they can use any of the Axxon Next VMS video analytics tools—detection of line-crossing, motion and stopping in a restricted area, loitering, abandoned objects, etc. The AxxonMomentQuest fast video search system is also based on metadata and does not require pre-configuring detection tools. The video search criteria are set on the fly (for example, find a red car in the parking lot), which makes it truly interactive. Video surveillance solutions “Our joint solution, without exaggeration, brings smart video surveillance systems to a new level of accessibility and cost-effectiveness. Initial investments are reduced due to significantly lower equipment costs. At the same time, the system stays current for a long time due to the continual development of Axxon Next video analytics and free updates,” notes Alan Ataev, AxxonSoft Global Sales Director. “We believe this Open Platform will gather all sorts of exciting new ideas and innovative solutions in the field and by combining our strengths we will benefit the industry as a whole and the world in general,” said James Wang, Deputy General Manager of Dahua Overseas Business. Openness, an essential element for modern collaboration and enhancing the surveillance industry, has always been a concept held dear to Dahua and is now being realised via DHOP. With a mission of ‘Enabling a safer society and smarter living’, Dahua will continue to focus on ‘Innovation, Quality, and Service’, to serve its partners and customers around the world.
ImmerVision, the inventor of the 360-degree panomorph lens and worldwide expert in immersive optical and imaging technology, announced recently that AxxonSoft Next is certified ImmerVision Enables 2.0. AxxonSoft joins more than 50 security industry ImmerVision-certified solution providers around the world in integrating The 360° Video Standard which gives the ability to instantly capture and navigate within 360-degree panomorph images. Equipped for future innovations 360-degree panomorph video from certified ImmerVision Enables 2.0 mini-domes, cameras, smartphones, tablets, wearables, and drones, can now be instantly processed by AxxonSoft Next VMS; allowing users to navigate 360-degree video content through a closed circuit or the cloud. In addition, users are provided with automatic recognition of new and existing panomorph lenses, cameras and mini-domes; automatic calibration; and automatic orientation recognition, without any extra software configuration. These innovative features accelerate the configuration process for integrating 360-degree panomorph hardware; enabling large scale deployments to be operational faster with the most effective 360-degree video coverage. “When the integration process is straightforward, our clients can focus on more important things. ImmerVision Enables 2.0 helps achieve this fluidity.” said Alan Ataev, Global Sales Director at AxxonSoft. “Also, as mobile devices converge with video surveillance, we can now dewarp 360-degree panomorph videos captured by certified ImmerVision Enables mobile devices like body worn cameras. We’ve taken the necessary steps to prepare for future innovations.” “AxxonSoft is synonymous with performance, reliability and efficiency.” said Joel Schaffer, Manager, Business Development, OEM/ODM Video Surveillance Applications at ImmerVision. “Now you can add panomorph compatibility to that list of descriptors as well.”
AxxonSoft is proud to have participated in Intersec for the fourth time, this year from 18 to 20 January 2015 in Dubai, UAE. This year's event saw version 4.0 of the Axxon Next VMS, as well as the Axxon Intellect PSIM platform for creating comprehensive and customisable site-specific security solutions. Visitors also saw the Auto Intellect road safety and vehicle monitoring solution alongside Face Intellect facial recognition. In addition to software, at its stand AxxonSoft showcased a Safe City project involving the company's software in Sharjah, the third-largest city in the UAE. Although the project is still in the implementation stage, the results of the system have already been praised by members of the police force of the Emirate of Sharjah, who shared their successful experience with AxxonSoft products. AxxonSoft software was also demonstrated at the stands of the company's partners, including such major Middle Eastern distributors as NIT and SNB. "Our stand was a hit with visitors. During Intersec we held fruitful talks with a number of partners, among these Abus, Axis, Bosch and NIT. We reached common ground on priorities and ways forward for deepening our relationships. In addition, during the event we announced the opening of a new office in Abu Dhabi. We hope that our success at Intersec 2015 will give the company extra momentum to push forward in the Middle East and outside it as well," – said Yuri Akhmetov, Director for Business Development in Middle East at AxxonSoft. "Intersec was extremely successful – we saw even more visitors than in previous years. We were pleased with great opportunities for partner engagement. We were able to show unique solutions and the new Axxon Next 4.0. There was huge visitor interest in the tentpole features of our Axxon Next VMS: Time Compressor, Tag&Track, and MomentQuest2. The Intellect PSIM also drew much attention, thanks to face and license plate recognition. We met with many government clients, such as police from Sharjah, Ajman and Fujairah, as well as with other delegates. So this was a case of having the perfect video management options available for clients, who have a demonstrated need for what only AxxonSoft is able to offer," – added Alan Ataev, Global Sales Director at AxxonSoft.