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Former UK biometrics watchdog’s new book argues AI surveillance can be deployed responsibly The use of AI in surveillance technologies has expanded both in number of deployments and the scope to which AI is applied, leading to new questions about how to use it in an accountable and ethical way. Former UK Biometrics and Surveillance Camera Commissioner and longtime Biometric Update columnist Fraser Sampson argues that AI surveillance can and must be deployed ethically and offers practical perspective on how to do so. His new book, How AI-Driven Surveillance is Changing our World: Do Robots Have the Right to Remain Silent?, expands on a series of essays first published in Biometric Update. It examines how citizens, policymakers and practitioners can understand the challenges posed by AI surveillance technology and its implications. Sampson draws on his experience in law enforcement, legal practice and regulation. Key considerations for controversial areas of policy and law enforcement are explored using real-life examples, and applying Sampson’s triptych analysis, which consists of what is technologically possible, legally permissible and societally acceptable. Since leaving the BSCC role in 2023 when legislation (that ultimately failed) to eliminate the position was tabled, Sampson has joined Facewatch in a non-executive director role. He is also an Honorary Professor and member of the Advisory Board at the Centre for Excellence in Terrorism, Resilience, Intelligence and Organised Crime research at Sheffield Hallam University. He previously served as the national chair of the Association of Police and Crime Chief Executives and CEO and solicitor to the Police and Crime Commissioner for West Yorkshire before being seconded as CEO to the Police, Fire & Crime Commissioner in North Yorkshire. With the UK among global leaders in deployments of real-time facial recognition by police and retailers alike, Sampson brings a unique perspective on balancing technological
Lee Introduces PROTECT Act to Prevent Online Child Exploitation July 23, 2026 WASHINGTON – U.S. Senator Mike Lee (R-UT) introduced legislation to shield children and other victims of sexual abuse from exploitation online. The Preventing Rampant Online Technological and Criminal Trafficking (PROTECT) Act requires platforms with explicit material to take reasonable steps to verify the age and consent of individuals who upload or appear in the content, while remaining consistent with First Amendment jurisprudence. “Pornography sites need to do more to prevent the rampant child exploitation that is occurring on their platforms. The PROTECT Act is a step in that direction,” said Senator Mike Lee. “This bill will verify the ages and consent of the people appearing in explicit content – stopping abusive material from ever getting uploaded in the first place.” Background The online pornography market has quickly become one of the most lucrative industries, but much of the material in circulation is the product of sex trafficking and child exploitation. Though law enforcement diligently investigates and prosecutes individuals who distribute child sexual abuse material (CSAM), pornography platforms regularly fail to verify the age, identity, or consent of depicted individuals. This carelessness allows human traffickers and websites to profit from underage or non-consenting individuals forced or coerced to participate. Senator Lee advocates for greater accountability in the online pornography market by proposing legislation that requires platforms to vet the content they distribute. Each safeguard imposed by the PROTECT Act creates an additional barrier to the circulation of exploitative material, reducing online sexual exploitation and image-based sexual abuse. Why This Matters Existing security measures demonstrate the technological and operational feasibility of implementing safeguards. Federal statutes such as 18 U.S.C. § 2257 prevent minors from appearing in sexually explicit material by mandating age verification and recordkeeping. Additionally, pornography platforms have begun
Face biometric image quality tool evolves with next ISO standard A new and improved version of the face biometric data quality measurement tool that is the reference implementation for the global face image quality standard is coming soon. The secunet development team behind OFIQ 2 is attempting to time the revised tool’s development with that of its associated standard, which is expected to be finalized by the end of 2027. The OFIQ (Open Source Face Image Quality) tool was discussed in a pair of recent European Association for Biometrics (EAB) events, one last week in collaboration with UNHCR, and the OFIQ user group meeting on Tuesday. Each was hosted by Christoph Busch, who is a member of SC37 Working Group 3 in addition to his work with ATHENE and Hochschule Darmstadt. Europe’s EES biometric border control system spurred interest in face image quality assessment, he notes. The ISO/IEC 29794-1:2024 standard for general biometric data quality was recently revised, Busch says, and it is being augmented with assessment methodology for demographic variability. For face biometrics, Busch reviewed the factors that go into data quality and how to evaluate the predictive value of quality assessments based on a comparison of errors versus discarded samples. OFIQ 2 is currently under development, and builds in demographic variability considerations. Other changes could include guidance on whether image distortion is caused by a defocused camera or subject motion. An independent evaluation of OFIQ by NIST was presented to the European Commission’s Joint Research Center (JRC) last week. The evaluation shows the false non-match rate falling as lower-quality samples are discarded in a test of 500,000 images from a visa database. OFIQ in operation The UNHCR is working on a research paper to present its findings using OFIQ thresholds for enrollments in operational settings. Business Analyst Ryo
Quick Navigation - Report Overview - Top Market Takeaways - By Component Analysis - By Application Analysis - By Deployment Mode Analysis - By End User Analysis - Key Market Segments - Regional Analysis - Drivers Impact Analysis - Restraints Impact Analysis - Investor Type Impact Analysis - Technology Enablement Analysis - Key Challenges - Emerging Trends - Growth Factors - Competitive Analysis - Future Outlook - Recent Developments - Report Scope Report Overview The Global On-Edge Face Matching Market generated USD 2.3 billion in 2025 and is predicted to register growth from USD 2.9 billion in 2026 to about USD 18.0 billion by 2035, recording a CAGR of 22.6% throughout the forecast span. In 2025, North America held a dominant market position, capturing more than a 34.3% share, with USD 0.8 billion in revenue. One of the main factors driving this market is the growing need for secure and low-latency biometric authentication. Organizations increasingly prefer identity systems that can process face data locally, reduce exposure of sensitive personal information, and deliver faster user verification. Another important driver is the wider use of edge AI hardware in cameras, smart devices, and access systems, which makes local face matching more practical across different security and authentication applications. On-Edge Face Matching market refers to facial verification systems that compare a person’s face directly on the device or at the edge, without sending all biometric data to a central server for processing. Demand for On-Edge Face Matching is increasing across enterprise security, workplace access, consumer electronics, digital identity, and smart infrastructure. Buyers want face matching solutions that are fast, privacy-focused, and able to work reliably even in environments with limited network support. Demand is also rising because many organizations now prefer biometric systems that combine local processing, stronger security controls, and a smoother
LOS ANGELES (KABC) -- Flock Safety bills itself as a public safety technology company, using license plate reading cameras to help law enforcement investigate crimes and locate missing people. But critics see something else - a growing surveillance network that has prompted concerns about privacy and how data is collected and shared. "The LAPD had to make a difficult decision of continuing -- in this case, discontinuing -- using Flock services until we can get those data, privacy, security and sharing concerns ironed out through a contractual relationship," Dean Gialamas, the Los Angeles Police Department's chief information officer, told ABC7. The LAPD recently ended its three-year partnership with Flock over those concerns. In an interview with ABC7, Flock co-founder and CEO Garrett Langley said he hopes the relationship will be restored. "We've got to tighten up the policy and make sure everyone is aligned and then turn it back on," Langley said. Even without LAPD as a customer, Flock still operates dozens of cameras throughout Los Angeles County and tens of thousands nationwide. Some residents worry the technology collects too much information. "Just knowing that there's cameras watching your every move -- I mean, even if I'm out walking my dog or anything, I think it's just a privacy issue," said Burbank resident Kimberly Forbes. Langley argues that's a misconception. "The technology is really simple," he told ABC7. "A car drives by, we take a picture. It's a static picture of a car, and then we read the license plate. That's what the technology is -- it's actually not that complicated, it's pretty simple." Flock says its system does not use facial recognition technology and does not identify who is driving a vehicle. The company says the license plate data captured is generally retained for 30 days, unless local laws
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Milwaukee Neighborhood News Service invites community members to submit opinion pieces of 500-800 words on topics of interest to central city Milwaukee. To send a submission for consideration, please email info@milwaukeenns.org. The views expressed are solely those of the authors. Milwaukee has become part of a mass surveillance apparatus. Surveillance technology is dangerous, and few know that these are counterinsurgency tactics being practiced on residents by our own police department. Integrated surveillance technology tactics, like drones, automatic license plate recognition (ALPR), video cameras, “Stingray” international mobile subscriber identity (IMSI) catchers, and social media trackers, were developed during colonial endeavors and on battlefields like Vietnam, Colombia and the Middle East to pacify local populations. These types of surveillance technologies made their way back for use against the domestic populace in the United States. The dangers of Flock cameras It’s unfortunate that the police have resorted to counterinsurgency tactics to surveil Milwaukee residents, but one is uniquely dangerous: Automated license plate reading technology, more popularly known as Flock cameras. Flock technology can establish a “pattern of life” for Milwaukee residents, especially when combined with other surveillance technologies, without a warrant or probable cause. A “pattern of life” is the recurring patterns, behaviors, and cycles that make up your average day-to-day activities. Establishing a pattern of life involves law enforcement collecting surveillance data and combining it to build a detailed picture of a person’s habits, routines, relationships and behavior. This includes where a person sleeps, when they leave, where they work, where they regularly meet, what vehicle they drive, which routes they take and much more. Flock cameras and other automatic license plate recognition tools also record other information, such as make, model, color, body style, temporary tags, damage and stickers. They call it the “vehicle footprint” and use it when there is
Abstract Facial Expression Recognition (FER) is a challenging problem in computer vision due to various factors, including illumination variability, occlusions, high intra-class similarity of expressions, and the complexity of accurately capturing subtle facial deformations. Traditional CNN-based models often suffer from spatial information loss and overfitting, especially when dealing with high-dimensional feature spaces. Furthermore, existing methods struggle to maintain performance consistency across real-time applications and diverse datasets. The proposed system introduces an AI-integrated, advanced FER framework based on a Hyperscale YOLOv5 Capsuled Convolutional Neural Network (YOLOv5c-CNN) combined with swarm intelligence optimization techniques. This novel methodology is structured into multiple stages to ensure high precision, robustness, and real-time performance in emotion detection from facial features. In the pre-processing stage, the input facial image undergoes normalization using a Non-Local-Median Collateral Filter (NL-MCF). This filter preserves edge integrity while minimizing noise and illumination variations, ensuring that essential facial features are retained for downstream processing. Subsequently, Adaptive Histogram Equalization is employed to enhance image contrast by computing the pixel intensity Cumulative Distribution Function (CDF), which further improves feature visibility in varied lighting conditions. The next stage involves Cross-Layer Slice Fragment Window Segmentation (CLSFWS). This segmentation technique isolates critical facial regions especially those prone to expression-induced deformations (e.g., eyes, mouth, brows) by detecting pitfall markings and slice-based layer variations. To tackle the high dimensionality of facial feature datasets and avoid overfitting, Adaptive Particle Swarm Optimization (APSO) is integrated as a feature selection mechanism. APSO dynamically selects the most relevant features by simulating intelligent swarm-based behavior, optimizing the feature space for improved classification accuracy and computational efficiency. The final classification and expression recognition are performed using the proposed Hyperscale YOLOv5 Capsuled Convolutional Neural Network (YOLOv5c-CNN). This architecture enhances the standard YOLOv5 model by integrating capsule layers, which preserve spatial hierarchies and relationships between facial features—offering superior recognition
Western Australia became the first Australian jurisdiction to scan crowds with live facial recognition technology — and to do so while the state's own privacy watchdog was locked out of the process. In the five weeks since Western Australia Police launched their mobile biometric trial on June 22, 2026, the technology has scanned more than 131,000 faces, generated 33 alerts, and contributed to 19 arrests — all before the state's Privacy and Responsible Information Sharing Act 2024 (PRIS Act) had fully come into force, and without any input from the independent regulator whose job it is to protect the public from exactly this kind of program. The state's Office of the Information Commissioner (OIC WA) confirmed in a formal statement on July 9 that it "was not invited to participate in any formal consultation process with WA Police and did not provide input into the design of the trial." That same watchdog now says the trial is the first real test of the PRIS Act — Australia's first law to directly govern how personal data is used in automated decision-making. The primary Information Privacy Principles under that Act came into force on July 1, 2026, nine days after the trial began. With further deployments scheduled for Joondalup on July 23 and Perth on July 24, the trial is continuing this week. How the System Actually Identifies People — and Why It Differs From Any Camera You've Seen Before The distinction between this technology and ordinary CCTV is not a matter of degree but of kind. A standard security camera passively records video; what happens with that footage is a separate decision, made after the fact, usually by a human. Live facial recognition is something structurally different: every face that enters the camera's field of view is actively identified in real
A shopper reaches for a cart, glances at the weekly deals sign, and strolls through the entrance. In the time it takes to pocket a phone, a camera has already captured that face, built an encrypted biometric template, and compared it against a store watchlist. This is grocery shopping in 2025, and it is already happening at several Grocery Outlet locations across the San Francisco Bay Area, according to reporting from KQED and Biometric Update. SAFR Guard launched in April 2025 as an AI-powered surveillance app built for retail loss prevention. Signs posted at participating store entrances inform customers the technology is active. That notification is, effectively, the full extent of shopper involvement in the decision. Grocery stores are starting to deploy a new system called SAFR Guard, it's a facial recognition software Here's how it works – A camera captures your face when you enter the store – It then turns your photo into a biometric map – It checks it against a private watchlist for… pic.twitter.com/1rRiOdRqsy— Wall Street Apes (@WallStreetApes) July 22, 2026 The mechanics are straightforward. An edge-computing camera scans faces at entry and checks each one against a watchlist built from retailer-submitted incident reports covering suspected shoplifters and violent offenders. SAFR reviews each submission before anyone is added. For cases involving violence or high-dollar theft, records can be shared across participating stores within the same geographic area — a neighborhood watch program, but with biometric teeth. Here is where SAFR's reassurances and its own policies begin to diverge. According to Biometric Update reporting, the data retention terms break down like this: - Non-match face templates are deleted within one second, per SAFR - Encrypted images of non-flagged shoppers are retained for up to 30 days - Local camera footage is stored for 30 days - Flagged
Urban management is rapidly shifting from reactive measures to real-time data-driven preventive management. AI-based smart city models that utilize vehicles operating daily in the city center—such as buses, taxis, and delivery trucks—as "mobile sensors" to constantly inspect roads and facilities are also becoming widely adopted. AI-matics, a company specializing in AI image recognition, is pursuing an AI-based urban data business in partnership with LG Uplus. The two companies plan to establish a system that detects road hazards and urban facilities in real time by combining automotive AI edge cameras with ultra-precision location technology. AI vehicles detect hazards throughout the city AI-MATICS supplies AI edge cameras and image recognition AI models for vehicle installation. Using a proprietary on-device AI method, it performs video analysis inside the vehicle without connecting to an external server, enabling real-time detection of potholes and facility anomalies. By combining this with LG Uplus's RTK (Real-Time Kinetic) positioning technology, detected locations are recorded down to the centimeter. This significantly reduces positional error compared to conventional GPS, enabling the immediate transmission of accurate location information to local governments and management agencies as soon as potholes or facility anomalies are detected. The targets detected by the AI include not only road hazards such as potholes, clogged drains, damaged manholes, and out-of-light streetlights, but also various urban infrastructure elements like road name signs, traffic facilities, illegal banners, and firefighting equipment. The accumulated data will be integrated with a smart city platform and utilized for facility management, preventive maintenance, and public asset management. The company explains that while facility management previously relied on fixed CCTVs and patrol personnel, limiting the scope of inspection, utilizing mobile vehicles enables continuous monitoring of a wide area, including alleyways. Through this project, AImatics is moving away from a focus on one-time equipment sales and expanding its
New Dedicated Viewfinder and Separate XLR Handle Unit Also Available SAN DIEGO, July 22, 2026 /PRNewswire/ -- Sony Electronics introduces the FX5, a new full-frame camera in its Cinema Line series. A newly developed fully stacked CMOS image sensor raises sensitivity performance[1] with 15+ stops of dynamic range, three base ISO settings[2], and a Dual Gain shooting[3] mode. For the first time in the Cinema Line FX series, the FX5 supports Open Gate shooting and in-camera recording in X-OCN, Sony's proprietary RAW format. It shoots 5K at up to 60 fps, 4K at up to 120 fps, and FHD at up to 240 fps. The result pairs the Cinema Line look[4] with production-ready operability in a compact, portable body. Also released are two optional accessories: a detachable OLED viewfinder and an XLR handle unit that records in-camera at up to 96 kHz, 32-bit float. "The FX5 builds on Sony's Cinema Line expertise, praised by cinematographers and video creators worldwide," said Yang Cheng, Vice President of Imaging Solutions, Sony Electronics Inc. "We wanted to build on the FX3, taking it one step further with the inclusion of some VENICE 2 features, like internal RAW recording and Open Gate. Features like these have been highly requested and will allow creators more creative freedom with an easier workflow." Availability and Price - ILME-FX5 with XLR Handle Unit will be available mid-August for a suggested retail price of $5,499.99 USD / $6,999.99 CAD. - ILME-FX5B body will be available mid-August for a suggested retail price of $4,899.99 USD / $6,299.99 CAD. Claudio Miranda, ASC, cinematographer of films including "Top Gun: Maverick" and "F1® The Movie," conducted a test shoot with the FX5: "I felt that FX5 is a camera that combines high quality image expression and mobility in a compact body, enabling people to
Manchester City confirm stance on facial recognition as supporters voice ticket identification concerns - Man City have confirmed no current plans to introduce facial recognition at the Etihad Stadium - The club’s stance comes amid ongoing supporter concerns over ticketing ID verification measures - City have introduced changes to ticket transfer policy for next season after talks with City Matters Manchester City have clarified their position on the introduction of facial recognition technology at the Etihad Stadium, confirming the club have no current plans to implement the system in response to supporter concerns over its potential use in ticketing and access procedures, as per a new report. The issue has gained renewed attention among the supporter base ahead of the 2026-27 season, with Manchester City having previously explored a facial recognition trial in 2019 before stepping back from the project, and more recent reports of updated turnstile infrastructure at the Etihad Stadium reigniting questions about the direction of the club’s matchday access policies. The Football Supporters’ Association had raised concerns after news emerged of new turnstile equipment at the Etihad Stadium that was capable of housing facial recognition cameras, with supporter groups warning that the scope of the system could expand beyond its stated purpose to encompass a broader and potentially more restrictive approach to ticketing enforcement. Manchester City’s new ticket scheme to help local supporters, through the eyes of football fans Manchester City have now moved to address those concerns directly, with communication from the club offering reassurance on the immediate position while acknowledging the wider context of a fanbase that has been increasingly vocal about the direction of the club’s ticketing policies over recent seasons. The clarification arrives at a moment when the club has also introduced a number of changes to its ticket transfer arrangements for 2026-27,
Vadzo Positions Onsemi AR0521 Based Falcon-521CRS Face Recognition Kiosk Camera for Fast Identity Matching and Contactless Passenger Verification Vadzo Imaging launches the Falcon-521CRS, aface recognition kiosk camera built on the Onsemi AR0521 sensor, delivering 5MP resolution, low read noise, high sensitivity color imaging, and wide-angle optical capability in a compact USB 3.0 UVC-compliant module designed for direct OEM integration into contactless passenger verification terminals at airports, transit hubs, immigration checkpoints, and automated boarding gates. FORT WORTH, Texas, July 22, 2026 (Newswire.com) - Vadzo Imaging announces the launch of the Falcon-521CRS, an Onsemi AR0521 5MP low noise USB camera purpose-built for face recognition kiosk deployments in high-throughput transit environments. Designed for OEM engineers and system integrators, the Falcon-521CRS delivers the sensor-level characteristics and interface architecture required to support reliable facial authentication at airports, transit hubs, and automated boarding gates without custom driver development. The Challenge of Reliable Face Capture in High-Throughput Transit Environments Transit hubs and airport check-in environments impose imaging constraints that generic camera products cannot consistently satisfy. A face recognition terminal at a boarding gate or immigration kiosk must capture sufficient facial detail at standoff distances that passengers naturally maintain during contactless interaction, typically between 30cm and 80cm from the sensor plane. At the same time the camera must function reliably across variable and often mixed lighting conditions found in airport halls, transit concourses, and outdoor check-in lanes, where ceiling-mounted fluorescent fixtures coexist with natural daylight and glass-reflected glare. A sensor with insufficient dynamic sensitivity produces underexposed captures in shadow-heavy interiors and blown-out images near windows, both degrading biometric inference accuracy. A narrow field of view forces a precise positioning requirement on the passenger, reducing throughput and increasing verification of latency. These requirements define a sensor and optical profile that most general-purpose USB camera products do not address within
City Xtra ·22 July 2026 In partnership with Yahoo sportsCity Xtra ·22 July 2026 Manchester City have clarified their position on the introduction of facial recognition technology at the Etihad Stadium, confirming the club have no current plans to implement the system in response to supporter concerns over its potential use in ticketing and access procedures, as per a new report. The issue has gained renewed attention among the supporter base ahead of the 2026-27 season, with Manchester City having previously explored a facial recognition trial in 2019 before stepping back from the project, and more recent reports of updated turnstile infrastructure at the Etihad Stadium reigniting questions about the direction of the club’s matchday access policies. The Football Supporters’ Association had raised concerns after news emerged of new turnstile equipment at the Etihad Stadium that was capable of housing facial recognition cameras, with supporter groups warning that the scope of the system could expand beyond its stated purpose to encompass a broader and potentially more restrictive approach to ticketing enforcement. Manchester City’s new ticket scheme to help local supporters, through the eyes of football fans Manchester City have now moved to address those concerns directly, with communication from the club offering reassurance on the immediate position while acknowledging the wider context of a fanbase that has been increasingly vocal about the direction of the club’s ticketing policies over recent seasons. The clarification arrives at a moment when the club has also introduced a number of changes to its ticket transfer arrangements for 2026-27, with the updated Friends and Family policy extending the pool of people Season Ticket Members can pass their ticket to – one of several adjustments made following consultation with City Matters, the club’s formal supporter engagement body. According to the Manchester Evening News, Manchester City have
90,000 Flock cameras have quietly gone up in the US: What they track and how to check your city Follow ZDNET: Add us as a preferred source on Google. ZDNET's key takeaways - Flock cameras are tracking vehicles across a shared network. - AI searches, cloud security, access, and false alerts are all risks. - Residents may not know they're installed until they spot them. By the time I learned that towns all around me in upstate New York had installed Flock "Falcon" cameras, they were already tracking every passing vehicle, including mine. In most of those communities, there had been little warning and no public discussion. Also: Ring's 'Familiar Faces': Why privacy experts worry it's mass surveillance in disguise I first noticed them because of what happened in Saranac Lake, a village near me. Residents protested last spring, officials were forced to reconsider, and the village ultimately voted to cancel its contract with Flock Safety. Soon after, the cameras came down. The same can't be said for many other US towns, where Flock's AI-enabled cameras actively surveil residents without clear consent. They're everywhere and easy to miss My small town, with a population of about 11,000, has several Flock cameras. I've spotted them on utility poles beside roads and intersections I regularly drive through, but they're admittedly easy to overlook or mistake for ordinary traffic cameras. Most look like small black boxes powered by batteries or solar panels, and they're connected through cellular service rather than Wi-Fi. Flock says more than 12,000 customers use its products, while public estimates suggest roughly 90,000 Flock-branded cameras may operate in the US. Police aren't the only users. Businesses, schools, and homeowners associations can install them, too. Flock Safety software can also be integrated with cameras from partner manufacturers, such as Motorola. While
BuzzFeed GamesOnly People With A Very, Very, Very, Very, Very, Very, Very, Very, Very, Very, Very, Very Good Eye For Color Can Solve Today’s HuedokuHuedoku #71! Halfway through the week — clear your head with today’s puzzle. ✨Posted 8 hours agocommentFacebookPinterestLinkby Crystal RoBuzzFeedBuzzFeed StaffHi, I’m Crystal, a Senior Editor based in Los Angeles and creator of BuzzFeed’s “That Got Dark” newsletter. Huedoku is a daily color puzzle with simple rules and a satisfying solve. It's like sudoku, but with colors instead of numbers. Sign up here to get notified every time we publish a new Huedoku! Come back tomorrow for Huedoku #72 — and share your score to challenge a friend! 🌈 🌈 New Huedoku drops every weekday at 4:00 a.m. PT / 7:00 a.m. ET. 🧩🗂️ Huedoku Archive — Every past puzzle, all in one place! Comments Comments
Sony has announced its new FX5. The FX5 is capable of recording 5K60 Open Gate (3:2) and 5K120 (16:9) internally in X-OCN RAW, and features three base ISO settings, a VENICE-inspired user interface, and a Multi-Function Dial. Even though it was designed to sit between the FX3 and the FX6, it represents a real paradigm shift for Sony as a company. I say that because the company has finally relented and made an affordable digital cinema camera that is capable of open gate recording. Up until now, Sony has been very careful in protecting its higher-end models, namely the BURANO and VENICE 2. However, with lots of the competition offering open gate in lower-end models, Sony arguably needed to change its thinking. The FX6 and FX3 were extremely successful cameras for Sony, but both of them are now getting a little long in the tooth. Instead of making new models of both those cameras, Sony decided to come up with something that sits in between. With the majority of sales happening at the lower end and more and more people creating content, this is arguably a smart move. Unlike the FX3, the FX5 isn’t a mirrorless hybrid, as it doesn’t feature any stills capabilities. I think most potential buyers of the FX5 won’t be angry about this, as it means fewer menus and less compromises on the video side. Besides, if you want a mirrorless hybrid, there are plenty of other options that are available. Key features - 5K 16.6MP Stacked Full-Frame Sensor - 5K60 Open Gate (3:2) & 5K120 (16:9) - Internal X-OCN Raw Recording - Triple Base ISO | Dual Gain Mode - 3.5″ 16:9 4-Axis Multi-Angle Touchscreen - AI-Powered Autofocus & White Balance - 5-Axis In-Body Image Stabilization - BIG 6 Menu System & Streamlined Controls -
USSOCOM seeks smartphone-based contactless iris biometrics for military ID The U.S. Special Operations Command (USSOCOM) is seeking companies and researchers that can turn ordinary Android phones and tablets into contactless iris collection devices capable of producing biometric images suitable for government identification systems. SOFWERX, working with USSOCOM’s Program Executive Office for Tactical Information Systems, plans to test whether cameras and lighting already built into commercial mobile devices can capture iris images of sufficient quality for matching and enrollment in the Defense Department’s Automated Biometric Identification System (ABIS). The effort could reduce or eliminate the need for operators to carry a separate iris camera or connect additional biometric hardware to a tactical mobile device. USSOCOM said its objective is to reduce the physical and power burden of biometric collection equipment while preserving the image quality needed for reliable identification. Organizations interested in attending an initial collaboration event must apply by August 28. Participation is limited to U.S. citizens. The in-person event will be held September 30 at SOFWERX in Tampa, Florida. SOFWERX was established through a partnership intermediary agreement between USSOCOM and DEFENSEWERX to connect the command with companies, researchers and other potential technology partners. The proposed study will examine Android phones and tablets with built-in cameras to determine whether they can locate an iris in an image without a separate optical attachment and capture it at a resolution suitable for biometric matching. Testing is expected to include image distortion, differences among individual cameras, and the devices’ sensitivity to near-infrared light between 805 and 1,000 nanometers. USSOCOM said a previous study indicated that mobile device cameras could perform iris localization, but the results need to be tested against a larger and more varied population. The command estimates that images from 500 to 1,000 people would be sufficient to establish whether the