Improvements in the technology have lowered – but not eliminated – concerns about false alarms False alarms have plagued the video analytics market since the beginning. Improvements in the technology have lowered – but not eliminated – concerns about false alarms. Companies providing video analytics systems say the question isn’t whether false alarms can be eliminated, but rather how they can be managed. “We’re still very far away from a day of zero false alarms,” says Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi). “Maybe someday when enough computing power is available and algorithms are at the level of sophistication of humans, but we’re still not there.” However, significant strides have been made in the last half dozen or so years, Ashani adds. Today when customers install the Agent Vi system and configure it, they can quickly reach a working state with mostly “true positives,” he says. In other words, false positives can be managed. The ability to achieve a workable level of false positives is “the difference between robust, high-end analytics and what you can get inside a camera at a low cost,” he adds. “People realize they can’t work with [in-camera analytics], so they come to us for a more reliable solution.” iOmniscient’s Nuisance Alarm Minimization System (NAMS) uses artificial intelligence to analyze what is or isn’t a threat – what’s a man or what’s a dog or what’s just a light changing? The system also helps to deal with the “noise” in a video image. “You never get to zero (false alarms), but if you reduce it several levels of magnitude, it’s tolerable,” says Dr. Rustom Kanga, CEO of iOmniscient. For example, if false alarms can be reduced from 20 a day to one every few days, it’s more manageable. "You never get to zero (false alarms), but if you reduce it several levels of magnitude, it’s tolerable" says Dr. Rustom Kanga, CEO of iOmniscient Kanga also contends there are times when false alarms are more tolerable because of the environment. For example, a face recognition analytic looking for shoplifters in the totally uncontrolled environment of a shopping mall might only be 70 percent accurate. However, identifying seven out of 10 in a crowd of 30,000 is better than 0 (and 3 out of 10 false positives is manageable). In markets that require perimeter protection and real-time alerting, there is still a lot of wariness about the success of video analytics, concedes Brian Lane, director of marketing, 3VR. In these markets, analytics need to be nearly 100 percent accurate for them to be useful; otherwise, security directors tire of all the false alarms and eventually turn the analytics off. In markets that require less accuracy, analytics are gaining ground, Lane says. For example, in business intelligence, analytics require less accuracy than, for example, identifying a former employee entering a building. Business intelligence relies on trends, not a single data point.
Combining thermal imaging with analytics provides a robust system Prices are dropping for thermal cameras. Now they are much more affordable for non-military customers – and more likely to be used in combination with video analytics. Combining thermal imaging with analytics provides a robust system; the technologies work well together. Thermal cameras make it easier to detect motion because you are eliminating much of the detail and only emphasising temperature “colors,” says Brian Lane, director of marketing, 3VR. When video analytics are tuned to be used with thermal cameras, alerts are only sent if there is motion with color signatures between 95 and 105 degrees F, for example. This removes motion from trees in the wind, birds, and other things that cause false positives. Thermography analytics have a host of uses within security and other industries. Thermal surveillance cameras can be combined with video analytics to deliver sophisticated image interpretation and comprehension for customers requiring detection in low-light or zero-light environments, says Maor Mishkin, director, Video Analytics Product Champion, DVTEL. DVTEL has developed the ioimage Thermal line as an automated detection solution for security deployments in critical infrastructure, perimeter security, oil and gas, and transportation markets. Analytic encoders allow the cameras to deliver an advanced level of analytic capabilities to reduce false alarms while maintaining a high probability of detection. Thermal imaging is ideal for a variety of low-light conditions, says Mishkin. The infrared detector senses the energy (or heat) that all objects, structures and people emit. This approach enables a more consistent image than traditional cameras in harsh environments, such as those affected by fog, haze, smog, smoke, rain and extreme variances in temperature. By combining video processing video analytics and raw video together in an edge device, you can get greater detection range – reducing costs – and greater detection accuracy, which increases security Thermal cameras sense heat and have always been known as the perfect “human detector” for night applications, says John Romanowich, CEO, SightLogix, Inc. Now they perform very well in bright sun and bad weather, making them an excellent choice for securing sites around the clock, he adds. SightLogix combines thermal cameras with video analytics and supported with sufficient video processing. The company’s smart thermal cameras now accurately detect intruders with very low nuisance alerts even in the most difficult outdoor conditions, says Romanowich. SightLogix’ camera systems use electronic stabilisation to compensate for wind and vibrations and geo-registration capabilities to create accurate size filters that ignore the movement of small animals, trash, trees, etc. They are ruggedised to withstand temperature extremes, weather, sand and dust. With the right system, video analytics can deliver excellent security results, Romanowich says. Thermal camera costs continue to fall even as video processing continues to increase, allowing customers to deploy military-grade intrusion detection solutions to solve general problems that include theft and vandalism, he adds. In effect, smart thermal cameras expand the function of a burglar alarm from inside the building out to the perimeter, with the same level of reliability and low costs that we expect from home/office systems. SightLogix takes a different approach from other video analytics manufacturers. First, SightLogix products are focused exclusively on the outdoor market. Second, the company has determined the only way to provide accurate video analytics outdoors is to apply a very high level of video processing in advance of the video analytics using the raw thermal video data as it leave the imager, all combined into a single edge solution. “This is the only way to make outdoor video analytics accurate, repeatable and cost-effective,” says Romanowich. SightLogix recognized that an edge-based approach that ties the imager, video analytics and video processing tightly together is mandatory when designing a system capable of overcoming outdoor variables. This is because once video has been compressed and sent over the network to a separate server for analysis, there is not enough video detail available to differentiate relevant motion – such as a human intruder – from irrelevant motion, such as trash or trees blowing in the wind. By combining video processing video analytics and raw video together in an edge device, you can get greater detection range – reducing costs – and greater detection accuracy, which increases security.
Analytics at the edge provide the ability to process what is happening in a field of view and discern if a relevant alert is triggered There are multiple benefits to using video analytics at the edge (i.e., near or inside the camera). For one thing, analytics at the edge provides the ability to process what is happening in a field of view and discern if a relevant alert is triggered. This can be faster and less expensive than the original video analytics model of using a separate dedicated server. However, there isn’t one right solution, as a video analytics' complexity and a camera’s processing power are not always aligned. Some analytics can begin the analysis at the camera and also utilize a server to balance the workload. Others may be best used in server-only models. Speed of alert is of importance, as results that are not urgent may not dictate a powerful camera. Another variable is whether the system needs actual video of an event or just information (metadata) from that video. When recorded video is not required at a server, intelligent cameras at the edge help lessen the required bandwidth, says Brian Lane, director of marketing, 3VR. He says intelligent cameras and the cloud go hand-in-hand. For example, only metadata is needed when counting people; therefore, intelligent cameras can do all the processing in the camera, and only the metadata is sent to the cloud. For security, only a low-bandwidth stream is sent to the cloud, while the high-resolution video is stored at the camera. When video is required, the edge advantage becomes far less, since the video must reach the server to be recorded, adds Lane. Having analytics such as face and demographics at the server level keeps the cost of the cameras low since the processor on the server does most of the work. Processing power on servers is far cheaper than having a robust processor in each camera. Analytics that require a lot of processing power greatly increase the cost of the cameras, since they must have a robust processor. When the processing takes place at the server level, the customer can keep overall costs down by using far cheaper cameras and using a centralized server-based system. Edge-based analytic cameras offer a host of benefits to facilities that need to monitor large perimeters, complex campus environments or geographically dispersed open spaces Sometimes, a combination is optimal. For example, Agent Vi has a patented approach that enables analytics processing both at the server and distributed to the edge. The Agent VI system operates on a server between the camera and the video management system (VMS), analyzing video streams and providing output of that analysis. A software module called “Vi Agent” runs inside video encoders and cameras at the edge (including brands such as Axis, Samsung, Hikvision, and Vivotek). The Agent Vi software completes “preprocessing” at the edge and sends information to the server, which completes the process and provides the output. Unlike strictly edge-based analytics, the approach is not limited by processing power and memory in the camera. Compared to server-only installations, the system is more scalable (by a factor of 10 to 20 compared to server-based systems), says Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi). The Vi Agent and server are the same for various verticals; various functionalities are activated per user based on license keys, with various licensing at different price points. Ashani notes a trend in the market of camera vendors turning their cameras into open platforms to allow software vendors to load analytics (and other applications) onto the cameras. Previously, software vendors had to work closely with camera vendors, even creating special software versions. “Today, the cameras are not yet at the level of an iPhone or Android [platform], but they are much more open and there is greater variety in terms of applications you can load,” he says. Ipsotek has always seen edge-based analytics as an interesting alternative to traditional server-based (centralized) solutions. Edge deployment lends itself to a distributed solution where infrastructure is not available, hence where transmitting video of high quality to a centralized server is not an option. Transport (road/rail) has been a major beneficiary of edge-based analytics technology, says Dr. Boghos Boghossian, CTO, Ipsotek. The lack of infrastructure results in a need for a more complex management of rules and possibly more challenging environmental aspects. In order to operate advanced video analytics solutions at the edge, a suitable hardware platform should be provided with enough processing power. However, often at the edge, the system must be rugged and should operate at high temperature extremes; consequently, the availability of such a hardware platform is less likely. There isn’t one right solution,as a video analytic’s complexityand a camera’s processing powerare not always aligned “Because of these issues, most manufacturers have opted to offer only basic analytics solutions at the edge,” says Boghossian. “Ipsotek took a different route, and through the use of digital signal processing technology, has managed to move its technology to the edge with no compromise to performance, feature list or robustness.” Ipsotek has been offering cloud-based systems to a number of large customers for a few years. The interesting correlation is the larger adoption of cloud-based solutions in projects based on edge analytics due to the lack of infrastructure and therefore reverting to cloud storage for data management. This trend may soon be overtaken by cloud-based video analytics, which is waiting for sufficient affordable bandwidth to stream video to the cloud at the required speed and quality. Edge-based analytics run on raw video data as opposed to encoded video on the server, allowing the analytics to gather more sensitive and accurate data, says Maor Mishkin, director, Video Analytics Product Champion, DVTEL. In addition, it allows the analytics to control the sensor and enable optimized video input for the analytic engine. Edge-based analytic cameras offer a host of benefits to facilities that need to monitor large perimeters, complex campus environments or geographically dispersed open spaces. Edge-based analytic devices do not rely on servers or third-party software. This reduces the network bandwidth requirements while maintaining performance at the highest level. In addition, when technology developers offer a complete solution that ties in edge analytics and video management, users benefit from a single, tightly integrated solution, which means there is less opportunity for failure, Mishkin says.
Retail has the greatest potential for analytics because it can be used both for security and for marketing & operations Video analytics isn’t just for security. In general, the ability to leverage data from video provides a new wealth of information and “intelligence” about all aspects of the business. The retail vertical is leading the way in reaping the benefits of video analytics beyond the security function. There are two reasons retailers have taken advantage of video analytics far more than other vertical markets. First, retailers generally face more theft than any other vertical market, says Brian Lane, director of marketing, 3VR. Analytics can help catch suspects by alerting in real-time. After the fact, analytics used for search purposes are far more effective to identify a theft than rewinding and fast-forwarding through video. Secondly, analytics can be used in retail to track customers, understand their age and gender, manage queue lines, know how long people dwell at an end cap, provide heat maps, etc. In short, retail has the greatest potential for analytics because it can be used both for security and for marketing and operations, says Lane. 3VR’s Customer Insights business is used by retailers, banks, food service, hospitality and other markets to track customers and understand buying habits. Through an interactive dashboard, retailers and others can harness 3VR analytics to provide business intelligence they can use to help increase sales or improve operations. Most of 3VR’s loss prevention and security products use some form of video analytics for forensic search capabilities, even if they only use a motion analytic. Using analytics for search greatly reduces the amount of time needed to find a suspect. Video analytics for POS & in-store operations management The latest security analytic at 3VR is aimed at any market where there is a point of sale or teller transaction. 3VR’s Customer Not Present analytic is integrated with the customer’s POS or teller system and requires a camera placed above the POS/teller. Each time a transaction takes place, 3VR’s VisionPoint VMS creates an event card with information about the transaction, such as items purchased, dollar amount, time/date, transaction number, account number, and other customizable data. The event card, when clicked-on, plays video of the event. If a transaction takes place without a customer present, the analytic will create a special event card marked as “Customer Not Present.” A manager can then search for all transactions in which a customer was not present to see if money is being stolen from the till, there are false returns, or other forms of employee theft. Analytics can be used in retail to track customers, understand their age and gender, manage queue lines and provide heat maps For the Customer Insights business, 3VR’s VisionPoint Queue Management software has added new features to detect average wait time, customer flow rate, and average queue size. There is also a customisable real-time dashboard that can notify store managers how many cashiers are needed now and how many cashiers will be needed in 30 minutes (or other customer time limit). For 3VR’s Customer Insights business, traffic is counted at the edge using 3VR’s People Counter, which results in far greater accuracy and less bandwidth, since video does not need to be sent to the server for processing. Only the metadata is sent, which requires very little bandwidth. Because of this, the data can be sent directly into the cloud where the data is parsed and available online at any time using a web browser to access 3VR’s VisionPoint Dashboard. The advantage to this method is that only the metadata is required.Analytics aids traffic and liability management in retail stores Other video analytics providers are also active in the retail environment. Agent Vi’s system can count people and measure foot traffic in a retail store, then aggregate the information and analyze the data. Even for retailers with multiple branches, Agent Vi provides a way to visualize traffic patterns in a store, to determine product placement, analyze how a change in store configuration might impact sales. Being able to respond immediately can help to promote return on investment (ROI) in the retail environment, especially related to managing liability. Dr. Rustom Kanga, CEO of iOmniscient, gives an example of someone who slips and falls in a shopping mall. “Now you can respond to the person immediately, ask if they’re OK, offer them a cup of tea,” says Kanga. “If somebody falls, and they think someone is taking care of them, they are much less likely to sue.” Responding immediately might mean the number of times people decide to sue would go down 80 percent, which reduces insurance costs. He notes the example of a shopping center owner with 200 malls that might have five slip-and-fall claims per week at each location, and many would just be “paid off” at $1,000 or $2,000 each. Responding quickly and with caring can lower the number to one claim per week, so it’s easy to do the math in terms of economic benefit – and ROI.
Intelligent searches of video archives provide investigators faster access to any needed video clip That video analytics can be immensely useful in forensics is relatively less known. However, forensic search capabilities offered by some modern video analytics solutions can not only save investigators significant amounts of time but also help them find results more accurately. These solutions leverage facial recognition and advanced object tracking, demographic analytics, license plate recognition capabilities and other such powerful features to take forensic investigation to a whole new level. Video analytics have earned a reputation as solutions that can provide real-time intelligence to enable immediate response. However, another aspect of video analytics is how the technology can be used for forensics. Basically, intelligent searches of video archives provide investigators faster access to any needed video clip based on the content of the video. It’s a monumental improvement over the old days of searching for hours while rewinding and fast-forwarding videotape. The use of video analytics for forensics is a less well-known benefit of the technology, says Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi). “Most people associate it with events, like detecting a person approaching a perimeter,” says Ashani. “But video analytics can also be useful in a forensic sense. It can help an investigator who needs to go into a video archive and find evidence of an event.” Defining queries with analytics speeds up forensic investigationAnalytics-based forensics enable investigators to define their queries. For example, a user might want to see all the blue trucks in an area in a specific time frame. “In seconds, we can provide results in terms of thumbnails – images that fit that query,” says Ashani. “They can zoom in and see what they’re looking for. Some customers understand this, and for some, it’s something new.” Most of the video recorded on an NVR/HVR (network video recorder/hybrid video recorder) is never viewed, says Brian Lane, director of marketing, 3VR. But, when the time comes that a short piece of video is needed and there are thousands of hours of recorded video, analytics can greatly simplify the task. ”For example, say you are looking for a male between 40 and 50 years old, wearing a red shirt, headed west,” says Lane. “Using analytics on a 3VR system, you can type these parameters into the search fields, and the system will send back video of the closest results. If you know the face of the suspect, using a face analytic makes the search even easier. In a world where time is money, analytics can be used to save countless hours searching through video.” Using facial, advanced object tracking, license plate, and demographics analytics, a user can search for color, speed, direction, size, age and gender, or a license plate number or a face 3VR’s VisionPoint VMS uses video analytics to greatly reduce the amount of time needed to search through video. Using facial, advanced object tracking, license plate, and demographics analytics, a user can search for color, speed, direction, size, age and gender, or a license plate number or a face. If a customer calls his bank to complain that money is missing from his account, an investigator can use 3VR’s VisionPoint VMS and type in the customer’s account number into the system. The system will display any video associated with a transaction using that account number. If there is video that doesn’t match that of the customer’s face, using 3VR’s face analytic, the bank can search through all of the bank’s video to see if the suspect has been in the bank using other stolen cards. The alternative is to get dates and times from the customer as to when they believe they were at the bank and search though thousands of hours of video. “Imagine how much video you would have to search through if the bank had 16 cameras and 90 days of storage?” says Lane. “If the bank has multiple branches, the investigator can also search across the various branches for the subject.” Tracking individuals and movements in forensic modeOne of Ipsotek’s latest generation developments is Tag and Track, a video content analysis-based tracking system that operates on a network of overlapping and non-overlapping CCTV cameras to track a “tagged” individual. In the forensic mode of operation, the system can be used to analyze hours of incident-related video footage in minutes to produce a detailed account of individual movements in the surveillance area. This product has the ability to identify behavior, selecting persons/objects of interest and enabling them to be tracked going forward. The system can also analyze where that person has come from, the path they have previously taken through the network and therefore where they have been. This system can analyze thousands of hours of video footage within minutes, therefore assisting greatly in investigations in which tracking evidence is essential. It is possible to search for a new face within historical data, providing information on when and where a new person of interest was in a facility over the previous month Facial recognition provides forensic capabilitiesAnother recent development is Ipsotek’s use of facial recognition technology to provide forensic functionalities. For example, it is possible to search for a new face within historical data, providing information on when and where a new person of interest was in a facility over the previous month. In an operational role, once a person has been tagged, the system takes over and automatically follows the person, intuitively waiting and reacquiring them should they disappear into areas not covered by the CCTV network. The system will also track the tagged individual backwards in time to show where that person has been. Tagging is either performed by operators using the Graphical User Interface or automatically with certain video content analysis and/or other if triggers (e.g., intrusion) have been satisfied or another sensor input trips (e.g., facial recognition). The system memorises the appearance of the tagged individual (based on a number of different visual identifiers) and tracks this collection of information. The Tag and Track system automatically learns the geometry of the camera network and understands where an object is likely to reappear when it goes out of one camera view.
The better the sensors, the better the analytics Garbage in, garbage out. The familiar cliché is just as applicable to the area of video analytics as any other field of computing. You simply must have a high-quality image in order to achieve a high-functioning analytics system. The good news is that video cameras, which are the sensors in video analytics systems, are providing images that are better than ever, offering higher quality – and more data – for use by video analytics. For analytics that require a higher resolution to achieve superior results, megapixel cameras provide video that allows for better face recognition, clearer license plate numbers, reliable age and gender of customers, and other uses. These help prevent false positives and increase reliability in forensic searches, says Brian Lane, director of marketing, 3VR. When Ipsotek considers a video analytics-based solution, 50 percent of that solution is reliant on the selection of the appropriate sensor (camera). With the emerging technologies of thermal, megapixel and advances in camera processing, this half of the solution is more readily achieved, says Dr. Boghos Boghossian, CTO, Ipsotek. In some areas like face recognition, the illumination of the face in challenging environmental conditions is key to the success of the solution. Therefore, Ipsotek has been evaluating cutting edge camera technology provided by Ipsotek’s technology partners to assist consultants and solution partners to design successful solutions for every growing video analytics market. The better the sensors, the better the analytics, agrees Dr. Rustom Kanga, CEO of iOmniscient, and lower costs of thermal cameras make them a good choice. However, cameras that provide higher-resolution images require more computing power, bandwidth, and storage, which complicates their use with analytics. In general, the resolution is downgraded to the least resolution possible to detect the activity the analytics system is looking for. For analytics that require a higher resolution to achieve superior results, megapixel cameras provide video that allows for better face recognition, clearer licence plate numbers, reliable age and gender of customers, and other uses iOmniscient has a new technology called IQ Hawk that “pulls out of the image what is important,” says Kanga. It accesses higher resolution only for areas of interest in the photo – such as using higher resolution of a face or licenseplate viewed from a distance to enable facial or license plate recognition. The rest of the image is used at lower resolution. If there are three people in a video frame, IQ Hawk presents all three faces in high-res to enable identification. “With IQ Hawk, we can dynamically look at an image at high and low resolution, based on what’s important,” says Kanga. In terms of using higher-resolution cameras with analytics, Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi), says it is important to consider the “lowest common denominator” in terms of usable resolution. For example, a megapixel camera might have a clearer image in good sunlight; but at nighttime, the image will suffer, and could be worse than a low-resolution image. “More pixels don’t mean more detection quality,” he says. “The more pixels you have, the more processing power you need inside the camera.” Therefore, high-resolution images may even be “downscaled” to a lower resolution for analysis to minimize the amount of data to be managed. Higher resolution can also introduce additional noise in many cases. Some higher-resolution cameras have video analytics built in. DVTEL’s new ioimage HD Analytic IP cameras provide HD broadcast-quality IP video coupled with built-in military-grade analytics. These high-resolution, low-bandwidth cameras, available in both HD 1080p and 720p, are optimized for outdoor conditions and available with predictable storage. The cameras have enhanced low-light and no-light capabilities, high sensitivity, and true wide dynamic range. A new analytics feature provides a reduced false alarm rate for people standing upright, which benefits applications that don’t need sophisticated detection of camouflaged or crawling intruders. ioimage analytics now have improved detection distance, which allows for fewer cameras needed to cover the same area.
The aviation and transportation industries are using video analytics to provide operational cost savings and performance enhancement Video analytics are now increasingly being used for the critical infrastructure, airports, transportation and city surveillance sectors, among other high-value markets. These markets need robust video analytics solutions that can be integrated into an overall security solution to deliver totally reliable results without any significant level of nuisance alerts. “We expect these markets to continue growing in hand with increasing advances in research and development for video analytics,” says Bill Flind, CEO, Ipsotek. Aviation and transportation industries are good examples where video analytics provide additional benefits including operational cost savings and performance enhancement, Flind says. Security personnel who were previously required to physically man certain areas can now be freed up to enhance security elsewhere on a site. Transportation and city surveillance sectors benefit from improved safety, compliance and business intelligence through early detection of potential hazards as they develop, triggering alerts for action before incidents occur. The market has been generally slow to adopt video analytics, says Flind. “We believe this is due to the historically disappointing results from many of the early technologies (that were over-promised and under-delivered),” he says. A good example is the many times when a “basic” system has been deployed onto what the customer had believed was a simple environment (e.g., perimeter fence of an airport or a power station), and then that system has become unusable because it generates hundreds (in some cases, thousands) of nuisance alarms each day. Flind adds: “The change that we are now seeing is that most potential customers now understand that a far more advanced technology will deliver an excellent solution into these environments – specifically, it is now widely understood that the power of a scenario-based solution like Ipsotek’s is required to deliver a robust solution even in these simple applications.” “What we are seeing now in the marketplace is that video analytics is being specified, but specified in a discerning and intelligent way, where the client and the client’s trusted advisors have an appreciation of the difference in the capability of the different technologies,” Flind says. 3VR’s VisionPoint VMS uses face, license plate, advanced object tracking, loitering and demographics analytics to search for suspects Ipsotek delivers scenario-based video analytics across a wide range of applications in the commercial and public sectors. Deployments include perimeter protection, intrusion detection, investigation and forensics, and the management of traffic, crowds and operations. The patented scenario-based approach creates an exact description of the target behavior, thereby giving dependable real alerts and dramatically reduced false alarms. Ipsotek has received “i-LIDS Primary” accreditation by the UK Home Office, signifying it is “deployable as the sole system for perimeter protection for sterile zone intrusion.” This recognition of quality and reliable video analytics provides assurance that high-security sites and projects will be monitored to the utmost level of protection. Installations include Transport for London (TfL) traffic management, London Eye, the O2 Arena, Network Rail, the Australian Parliament, plus various international airports and other critical buildings and infrastructures around the world. Meeting Stringent Customer Requirements Another video analytics provider, Agent Vi, is strong at the mid- to high-end of the market, where customer requirements are more stringent. Vertical markets include critical infrastructure and transportation hubs (including airports, seaports, train stations and railroad operations), the enterprise market, and retail. Agent Vi’s rules-based system includes some preconfigured types of objects the system can detect and behaviors it can analyze. The integrator can specify the analytics rules needed on a per-camera basis. For example, one camera might alert if a crowd forms and another might alert if a vehicle stops in the area. A user interface allows operators to set the rules, or they can rely on a systems integrator to set the system up. In the enterprise market, applications might include perimeter security, or detecting people where they shouldn’t be, or detecting tailgating through access control points. Analytics can address safety issues, such as detecting if something is blocking an emergency exit or a vehicle is parked in a no-loading zone. “We provide a fairly extensive tool box, and a lot of times we don’t know the exact configuration or application,” says Zvika Ashani, chief technology officer (CTO), Agent Video Intelligence (Agent Vi). “It’s so versatile.” Video analytics company iOmniscient is active is 30 vertical markets, including transportation (airports, railways, seaports), retail banking, hotels, casinos, the Secret Service, Defense Department, etc. The company is also active in Smart City applications, including Singapore and other locations in the Middle East and Asia. In the North American market, iOmniscient supplies the Chicago Transit Authority, the Mexico City airport, prisons in Vancouver, various oil and gas applications, universities, museums, etc. iOmniscient systems can operate centrally or at the edge, depending on the application. However, at the edge, the software is installed in a black box alongside the camera rather than in the camera because chips inside cameras do not have enough computing power. “When we say edge, we mean near the camera not in the camera,” says Dr. Rustom Kanga, CEO of iOmniscient. Consider Overall System Costs In assessing the costs of video analytics, the traditional practice of considering costs “per camera” is no longer relevant. Rather, the cost of the entire system should be considered, and also how it might be offset by cost savings achieved in other areas. Kanga contends one Smart City application was completed at zero incremental cost – the cost of the system was offset completely by a 70 to 80 percent reduction in storage, bandwidth and computing requirements. “The hardware is half the cost of the system, so if you can reduce it by 80 percent, the whole system can come in at zero incremental cost,” he says. “Our system is very cost-competitive.” "If you don’t have video analytics, you are wasting your money putting in cameras" “If you don’t have video analytics, you are wasting your money putting in cameras,” says Kanga. “If you have 1,000 cameras in a large environment, no one will sit and watch them. They are only useful after the event. Video analytics enables systems to become a useful tool to prevent incidents and to allow a fast response. With video analysis, video becomes a tool that you can use in real time.” Analytics are used to solve a specific problem, says Brian Lane, director of marketing, 3VR. For example, when there are bandwidth restraints, cameras can be set up to send only low-bandwidth video until the analytic detects a car or person. The analytic tells the camera to then send a high-resolution stream to the server for the duration of the event. This helps keep bandwidth and storage requirements low. 3VR’s Customer Insights business is used by retailers, banks, food service, hospitality and other markets to track customers and understand buying habits. Through an interactive dashboard, retailers and others can harness 3VR analytics to provide business intelligence they can use to help increase sales or improve operations. 3VR’s VisionPoint VMS loss prevention and security video management software (VMS) uses face, license plate, advanced object tracking, loitering and demographics analytics to search for suspects. The price of analytics is dropping, and many companies are lowering the barrier to entry by allowing customers to pay monthly or yearly, rather than all at once, says Lane. But, while implementing analytics has become easier, many integrators are not trained on how to set up and install analytics, leading to a frustrated customer. 3VR has specific tried-and-true methods for setting up cameras for analytics, and its integrators are trained on analytic implementation through online and on-site classes. 3VR provides the hardware for highly accurate people counting, and customers can pay for retail analytics monthly. Proactive Perimeter Security According to DVTEL, video analytics provide an ideal solution for proactive perimeter security in the critical infrastructure, transportation and commercial/industrial verticals, as well as general security for healthcare, gaming and other facilities. Going beyond the typical forensic video capabilities, analytics can help users catch criminals during a security event. The technology provides the best ratio of false alarm rates to probability of detection, as well as the most reliable and cost-effective solution for intrusion detection, when compared to legacy perimeter and fence sensors, typical surveillance devices and other video content analysis solutions. DVTEL’s Site Viewer eliminates the need to use a Video Management System to monitor and control remote sites. This makes it suitable for remote sites that cannot install a PC (such as power utility installations, solar farms, cellular and communication facilities, and construction sites) and that have limited network bandwidth. Today’s most effective security systems incorporate other sensors, including perimeter intrusion detection, alarms, remote video monitoring thermal imagery and video analytics, says Maor Mishkin, director, Video Analytics Product Champion, DVTEL. In today’s market, end users demand integrated systems that combine intelligent detection systems to specifically fit their business and risk profile, he adds. By streamlining decision-making and even automating some protocols, video analytics enable organizations to respond more quickly to events By streamlining decision-making and even automating some protocols, video analytics enable organizations to respond more quickly to events, using fewer personnel than would be required with traditional surveillance systems. In addition, ioimage video analytics enable more accurate detection and fewer false alarms by reliably differentiating between legitimate threats and other movement, such as tree branches blowing in the wind. Perhaps most compelling, video analytics has the potential to decrease storage costs for many users, since they are able to record at lower resolution until the system detects suspicious movement. Tight Integration at the Edge High-profile perimeter security breaches at critical sites have underscored the risks associated with physical security breaches and the potentially disastrous consequences. Now organizations – some as a result of pending regulations such as NERC CIP for utilities – are seeking reliable and cost-effective solutions using video analytics to detect intruders and send alarms about security incidents in real time. SightLogix SightSensors are smart thermal cameras with embedded video analytics powered by a high degree of video processing. By tightly integrating the imager, analytics and video processing, SightSensors are able to deliver accurate detection in all weather, climates, and conditions. Some verticals adopting video analytics for outdoor intrusion detection include electrical utilities, specifically substations; airports and other transportation organizations, such as bridges and rail applications; datacenters; and ports. These sites require protection and 24/7 detection for large, open areas that are difficult to patrol. Video analytics with thermal detection cameras combine detection with video verification in a single solution, allowing for a fast and precise response. Beyond security, video analytics combined with outdoor thermal cameras opens up a new world of understanding, from early detection scenarios to looking at behavior that increases operational efficiency.
Artificial Intelligence: Understanding Its Place In Physical SecurityDownload
Delivering Smart, Secure and Healthy Retail Environments with the CloudDownload
Protecting Your Data Against Physical ThreatsDownload
Achieving True Situational Awareness In Operation Centers With Computer Vision & AIDownload