Coles and Woolworths test facial recognition technology In short: Coles and Woolworths have tested facial recognition technology in a bid to combat retail crime. Neither of the supermarket giants have said if it would be rolled out in their Australian stores. It comes after Bunnings won a legal battle to monitor its customers with AI. Coles and Woolworths have conducted tests of facial recognition technology, but it is unclear if either supermarket will be implementing it in stores. It comes after the Australia Financial Review reported both Coles and Woolworths had trialled the technology as part of an ongoing effort to combat retail crime. The article said both supermarket giants had "conducted early testing" of the technology. When the ABC asked Coles about the potential of it being rolled out in stores, a spokesperson made a distinction between the use of the term "test" instead of "trial". "Coles has not done a trial using this technology," the spokesperson said. "A small, one-off, controlled proof-of-concept test of the technology was undertaken which did not use customer or team member information or data. "No decision has been made about the deployment of facial recognition technology." The spokesperson said Coles did not currently use facial recognition technology in stores. The ABC understands Woolworths tested the technology in its New Zealand office. A Woolworths spokesperson did not address the ABC's questions on how facial recognition technology was tested or if it would be used in Australia. "Keeping our team and customers safe is the most important thing we do and we've put significant investment towards this," the spokesperson said. "While our current safety initiatives are making a difference, we are still seeing a concerning amount of aggression and conflict incidents in our stores on a daily basis, including weapons being presented." Facial recognition technology
Aug 18, 2026 · via abc.net.au
Privacy advocates have long had reservations about biometric facial scanning, but some businesses still haven’t gotten the memo – with grocery chains now reneging on promises to avoid biometrics and a major EFTPOS supplier spruiking a terminal that lets you pay by scanning your face. Verifone, which has over 300,000 EFTPOS terminals in everyday use, this month introduced Australian customers to its Victa model, which embraces biometric scanning alongside normal tap and pay features. Customers enrol their biometrics once through merchants, digital wallets, banks, and other companies, with the technology creating a unique digital token that cannot be used elsewhere or reverse engineered to recreate the original face or handprint. By looking into a camera on the device, or scanning their palms to capture the unique pattern of veins in their hands, customers verify their identity against the token data, completing financial transactions or identifying themselves as a member of the store’s loyalty program. It’s part of a suite of products that let merchants sell with back-end integration to e-commerce platforms like Shopify, Bilt, Aevi, PayPal, and Stripe – and the ability to, as Verifone head of strategic partners Kristy Gregory put it, “pay with a smile.” “People already use biometrics to unlock phones, access apps, and confirm payments online,” she said. Verifone is “giving customers that same choice at the point of sale” with a tool that makes checkout “faster, easier and safer for consumers and retailers,” she added. A hard sell for privacy-focused consumers? Retailers may love the cachet of offering biometric capabilities for consumers, but those customers have consistently proven more wary of other technologies built around biometrics. Biometric systems “are becoming more effective as technology advances [but] they are not a foolproof method of authentication or identification” as spoofing, false acceptance, and other issues persist, the
Aug 18, 2026 · via ia.acs.org.au
Microsoft ends support for Internet Explorer on June 16, 2022. We recommend using one of the browsers listed below. Please contact your browser provider for download and installation instructions. August 18, 2026 NTT's paper was accepted at ICPR 2026, the International Conference on Challenges in the Fields of Pattern Recognition, Computer Vision and Machine Learning, to be held in Lyon, France from August 17, 2026 to 22nd. The adopted papers are as follows. Abbreviated names of the laboratories: HI: NTT Human Informatics Laboratories Shogo Sato (HI), Kazuhiko Murasaki (HI), Ryuichi Tanida (HI) We propose a training-free and low-cost rendering method for generating photo-realistic images from colored point clouds. Colored point clouds captured by LiDAR are sparse, so they are not suitable for producing high-quality images directly. In our method, we first upsample the point cloud and geometrically assign 3D Gaussian Splatting parameters to each point. This enables dense and natural image rendering. We also use pre-trained models to restore missing or blurry regions. In addition, multi-view refinement helps recover structures that are difficult to reconstruct from a single view while maintaining geometric consistency. Experiments show that our method achieves rendering quality comparable to conventional learning-based methods without requiring training data and with lower computational cost. Information is current as of the date of issue of the individual topics. Please be advised that information may be outdated after that point. WEB media that thinks about the future with NTT
Aug 18, 2026 · via group.ntt
Merlin Bird ID is an app likened to Shazam for birdsong, and it taps into the world's largest database of bird sightings, sound and photos to share a fun way to identify birds. With this free app from the Cornell Lab of Ornithology, users can ask simple questions, explore birds in their region, upload photos, and record singing birds to learn something about the natural world. "Birding" is no longer a pastime for retirees, since Gen Z is increasingly picking up birdwatching as a low-cost, low-pressure way to unplug and be present outdoors. On TikTok, #birdwatching, #birdtok and #birding content are only becoming more popular. After discovering the hobby through social media, this younger, unexpected group is finding themselves quickly drawn in to its mix of mindfulness, mild adventure and the dopamine hit of seeing or hearing something rare. Bird Identification Apps Merlin Bird ID Helps with Identifying Birds Seen and Heard Trend Themes - Audio-driven Nature Recognition — AI-powered sound matching turns casual outdoor moments into instant learning experiences, creating openings for platforms that identify biodiversity through ambient audio. - Gen Z Birding Culture — Social media is reshaping birdwatching into a youthful wellness hobby, revealing potential for community tools that blend nature discovery with digital sharing. - Mindful Micro-adventures — Low-cost outdoor activities are gaining appeal as accessible alternatives to screen-heavy leisure, supporting new services centered on calm exploration and local discovery. Industry Implications - Mobile Applications — Feature-rich identification apps can expand beyond utility into habit-forming discovery ecosystems that combine AI, education and user-generated data. - Outdoor Recreation — The rise of casual birding signals demand for approachable gear, guided experiences and beginner-friendly formats that make nature participation less intimidating. - Education Technology — Interactive species recognition creates fresh possibilities for informal science learning, where real-world observation
Aug 18, 2026 · via trendhunter.com
Bastrop’s Flock camera policy could soon include additional safeguards and a shorter data retention period. The overview During an Aug. 11 meeting, Bastrop City Council directed staff to return with an updated Flock policy, including additional safeguards. City Manager Sylvia Carrillo-Trevino said it would add “checks and balances,” comparing the goal to ensuring “the cashier isn’t also the one taking the money to the bank.” On Aug. 13, Flock announced it cut the default data retention period from 30 days to seven. Community Impact reached out to city officials to learn if the new recommendation would be part of the changes. Bastrop Police Chief Vicky Steffanic said her department follows Flock's default data retention period, confirming Bastrop's retention period will also be recommended to change from 30 days to seven days. What else? Although officials would not provide details about what specific policies are under review, Steffanic said the BPD's rules are "consistent with applicable best practices and comply with requirements established by the state." "Any potential changes to the department’s current policy are presently under review," Steffanic told Community Impact. "At this time, no specific changes have been approved or implemented." What we know According to the city's current policy, Flock can only be used for: - Criminal cases: Searches must be tied to a criminal investigation - No facial recognition: Cameras only capture license plate information - Enforcement limits: Not used for citations or minor offenses Looking ahead The policy is expected to return to Council on Aug. 25. Before you go BPD is not the only local law enforcement agency using camera-based technology. As previously reported by Community Impact, Bastrop County Commissioners Court approved on March 24 a one-year, $17,100 Clearview AI licensing agreement for facial-recognition software that officials said can help identify people involved in cases
Aug 18, 2026 · via communityimpact.com
Do these creepy patent drawings reveal what’s next for Meta’s smart glasses? “Pervert glasses” that remember faces. Cute. - A new Meta patent shows smart glasses using facial recognition to scan a dinner party and pick out who's worth filming. - The AI reads expressions and actions, then auto-creates personalized highlight reels and searchable memories of people met. - It's just a patent, not a confirmed feature – but the illustrations are likely to unnerve privacy advocates. - Meta is already facing backlash over the glasses: facial-recognition tool NameTag was scrapped in June, and courts in UK and New York have banned the specs. Key Takeaways by nexos.ai, reviewed by Cybernews staff. Eerie drawings in a newly published Meta patent application show smart glasses scanning guests at a dinner party, recognizing their faces – and deciding who is interesting enough to film. The application, filed by Meta Platforms Technologies – the maker of Meta's Ray-Ban smart glasses and VR hardware – describes an AI camera system that identifies people via facial recognition, interprets their actions, and turns what it sees into personalized media and searchable memories. The latest application was filed on February 4 2026 and published on August 13. It is a continuation of earlier filings, meaning some of the underlying technology has been in Meta’s patent pipeline for years. And the patent’s illustrations show just how invasive technology could become if applied to Meta’s glasses business, which, to date, has sold around 7 million pairs. Figure 5A depicts someone wearing AR glasses at a dinner party. The system analyzes the people in the room, uses facial recognition to identify one guest as the wearer’s wife and selects her as a “point of interest.” Continuing the fun, Figure 5B shows the camera automatically zooming towards the wife, centering her
Aug 17, 2026 · via cybernews.com
Woolworths has been running a trial of facial recognition technology at its New Zealand office, as the supermarket giant explores using it in its Australian stores. A spokesperson for Woolworths told 1News the technology had been tested at its support office in Auckland to "further understand the use of this technology to improve safety". “While our current safety initiatives are making a difference, we are still seeing a concerning number of incidents of aggression and conflict in our stores on a daily basis, including weapons being presented." They said that between 2019 and 2025, acts of violence and aggression had increased by 238%. "We have also seen a shift from opportunistic shoplifting to more brazen confrontations often involving weapons, threats to kill, and physical violence." They said the corporation was "still at an early stage" and could not comment further. The test comes after a February ruling by Australia's Privacy Commissioner that gave hardware giant Bunnings the green light to use facial recognition, following a previous ruling that found it had breached privacy laws. Facial recognition technology is already being used in New Zealand. Bunnings has rolled it out across its network, while Foodstuffs, which operates New World, Pak'n'Save, and Four Square, has also implemented it at some locations. Briscoes Group, which is behind Briscoes and Rebel Sport, has been running a year-long trial of the technology at its stores. Before using facial recognition technology, the New Zealand Privacy Commissioner said organisations must justify its necessity, ensure the problem is serious, and check whether less intrusive alternatives would work. SHARE ME
Aug 17, 2026 · via 1news.co.nz
Abstract Artificial intelligence for medical imaging is required to be accurate and interpretable to clinicians. However, current multimodal biomedical foundation models often prioritize performance over explainability. Here we present ConceptCLIP, an explainable biomedical foundation model that achieves state-of-the-art diagnostic accuracy while delivering human-interpretable explanations across diverse imaging modalities. We curate MedConcept-23M, a large-scale dataset comprising 23 million biomedical image–text–concept triplets. Leveraging this dataset, we pretrain ConceptCLIP via joint image–text and region–concept alignment for precise and interpretable medical image analysis. Across a large-scale benchmark covering 78 datasets in 10 imaging modalities, ConceptCLIP demonstrates superior diagnostic performance while providing human-understandable explanations. In a clinician user study spanning three modalities, the concept-based explanations provided by ConceptCLIP help clinicians verify model predictions and identify potential errors. As an explainable biomedical foundation model, ConceptCLIP represents a critical milestone towards the widespread clinical adoption of AI, thereby advancing trustworthy AI in medicine. This is a preview of subscription content, access via your institution Access options Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Subscribe to this journal Receive 12 digital issues and online access to articles $119.00 per year only $9.92 per issue Buy this article - Purchase on SpringerLink - Instant access to the full article PDF. USD 39.95 Prices may be subject to local taxes which are calculated during checkout Data availability This study incorporates a total of 79 datasets. Among these, the proposed MedConcept-23M dataset is used for training the ConceptCLIP model. The image part of the pretraining dataset, MedConcept-23M, is open-sourced and can be obtained directly from the publicly available PMC Open Access Subset (PMC-OA). The captions and concepts are available at https://huggingface.co/datasets/JerrryNie/MedConcept-23M. To enable reconstruction of the full dataset, we provide a dataset reconstruction script as part of
Aug 17, 2026 · via nature.com
Supermarket duopoly tests facial recognition
Coles and Woolworths have conducted tests of facial recognition technology that they could use in their Australian supermarkets to combat crime, although it is not clear whether they will implement it fully.
Dr Jason Pallant, a marketing expert at RMIT University, said the trials posed a “security versus privacy dilemma” (The Guardian).
Tom Sulston, the head of policy at Digital Rights Watch, flagged that facial recognition was “wildly inaccurate”, and also raised concerns that Coles and Woolworths wouldn’t be able to control the way their biometric data was used (The Guardian).
Both Coles and Woolworths say they have not decided whether to deploy the technology after the trials. “Keeping our team and customers safe is the most important thing we do, and we’ve put significant investment towards this,” a Woolworths spokesman said (AFR).
The testing revelations follow hardware chain Bunnings’ legal battle win earlier this year that allowed it to monitor its customers with artificial intelligence (ABC).
Aug 17, 2026 · via thesaturdaypaper.com.au
“The Federal Circuit concluded the reference ‘logically would have commended itself to an inventor’s attention in considering his problems.’” The U.S. Court of Appeals for the Federal Circuit (CAFC) issued a precedential decision on Friday, August 14, in The Nielsen Company (US), LLC v. TVision Insights, Inc., affirming a Patent Trial and Appeal Board (PTAB) final written decision that invalidated challenged claims of a Nielsen audience measurement patent as obvious. The court rejected arguments that the Board improperly relied on a scientific publication as analogous prior art and that the publication failed to disclose the claimed resolution reducing and facial recognition steps. TVision Insights, Inc. filed a petition for inter partes review (IPR) of U.S. Patent No. 11,470,243, owned by The Nielsen Company (US), LLC, titled “Methods and Apparatus to Capture Images.” The patent relates to systems for measuring and identifying the audience of a media presentation device such as a television. The specification describes a camera-based system that uses a “people counter” to detect audience members based on features such as heads and faces in low-resolution images. A “person identifier” then compares the detected faces against stored facial signatures using higher-resolution images. TVision’s petition challenged 14 claims, but Nielsen disclaimed the 3 independent claims at issue in its preliminary response, and the Board instituted review of 11 dependent claims, with claims 4 through 6 becoming the focus of the appeal. Claim 4 recites processor circuitry that reduces the resolution of a first image to obtain a reduced resolution image and determines head orientation based on that image. Claims 5 and 6 add a two-step process that generates a facial signature from a separate image corresponding to the head location identified in the reduced resolution image, then compares that signature against a database of stored signatures. The Board considered two
Aug 17, 2026 · via ipwatchdog.com
Offering a variety of advertising and sponsorship options for reaching influential specialists from targeted demographic splits.
Cureus provides an equitable, efficient publishing and peer reviewing experience without sacrificing publication times.
Generate broad awareness and deliver relevant, peer-reviewed clinical experiences directly to potential customers.
Dedicated Cranial Radiosurgery: Clinical Experience with New & Innovative SRS Technologies
Sponsored by Zap Surgical Systems
Real-Time Adaptive Motion Management on Helical and Robotic RT Platforms
Sponsored by Accuray, Inc.
Cureus Journal of Medical Science
Sponsored by Zap Surgical Systems
Sponsored by Accuray, Inc.
You can unsubscribe anytime.
By joining Cureus, you agree to our Privacy Policy and Terms of Use.
Aug 17, 2026 · via cureus.com
Researchers at the Institute of Fundamental and Frontier Sciences, University of Electronic Sciences and Technology of China have combined boson sampling, a quantum process with experimentally verified advantage over classical computers, with neural networks to improve machine learning classification. The team developed a hybrid framework where a neural network compresses data features onto a boson sampling circuit, generating quantum states that enhance support vector machine performance. Using four datasets with various classes, the model outperformed classical linear and sigmoid kernels, demonstrating the potential of boson sampling-based quantum kernels for practical quantum-enhanced machine learning. Hybrid Boson Sampling-Neural Network Architecture for Enhanced Classification The core innovation lies in a neural network’s ability to compress complex data features, preparing them for processing by a programmable boson sampling circuit. This approach addresses a significant hurdle in quantum machine learning: the high dimensionality of practical datasets. The team’s framework utilizes the neural network to reduce the number of features needed for analysis, bridging the gap between large, complex data and the limitations of current quantum hardware. The resulting quantum states, generated by the boson sampling circuit, span a high-dimensional space, enabling improved classification performance. The researchers tested their model against four distinct datasets, Ionosphere, Spambase, MNIST, and Fashion-MNIST, each containing various classes of data, and the hybrid model outperformed classical linear and sigmoid kernels in these tests. The researchers found that achieving enhanced accuracy depended on utilizing a sufficiently expressive boson sampling circuit, with expressivity controlled by both the number of modes and injected photons. This suggests a pathway to optimize the quantum component for specific classification tasks. Mohammad Sharifian explained in their published work that “the integrated architecture of classical neural network with quantum boson sampler enhances the accuracy of SVM image classification outperforming both classical linear and non-linear sigmoid kernels as well as
Aug 17, 2026 · via quantumzeitgeist.com
Meta files patent for AI facial recognition glasses that identify people around you and record automatically A newly published patent from Meta suggests smart glasses could recognize faces, detect laughter and more Imagine hosting a dinner party without stopping to pull out your phone. Later, your glasses present you with a collection of photos and video clips showing your partner across the table and your friends laughing together. That's the idea behind the system Meta has patented for it's Meta glasses. The patent filing describes camera-equipped glasses that use facial recognition, expression analysis and information about your relationships to identify the people around you and decide which moments you may want to keep. The glasses could even ask, “I’ve generated some highlights of tonight’s dinner party. Would you like to see them?” At a time when Meta is continuously under fire for it's "pervert glasses" the patent sounds convenient for some, but also a potential privacy nightmare. How Meta’s glasses could choose what to capture The patent, published Thursday and first reported by 404 Media, describes a system that looks for “points of interest” within the wearer’s field of view. At a dinner party, facial recognition could identify the wearer’s wife and place her in the center of the frame. Other guests could be cropped out or blurred in the background. The system could then analyze facial expressions. If two people start laughing, for example, the glasses could recognize that reaction and reposition the camera to focus on them. Who makes the final cut may depend on the wearer’s relationship with each person. According to the report, information from a user’s social graph could help the system determine which friends or family members are likely to be more interesting to them than other people in the room. Get instant access
Aug 17, 2026 · via tomsguide.com
260814-N-CF730-1023 U.S. Navy Capt. Brian Bungay, commanding officer, Naval Base San Diego (NBSD), left, presents awardees with a challenge coin during the Presidential Physical Fitness Award presentation at Murphy Canyon Youth Center, Aug. 14, 2026. The Presidential Physical Fitness Award is a national recognition program designed to encourage physical fitness, strength, and healthy habits among youth. NBSD recognize excellence in physical fitness as one of the select bases across enterprise to pilot the revived program. Established in 1922, NBSD is the largest West Coast naval installation and principal homeport of the Pacific Fleet, supporting more than 60 combatant and auxiliary surface ships and more than 250 shore commands. (U.S. Navy photo by Interior Communications Electrician 2nd Class Ulrika Mendiola) | Date Taken: | 08.14.2026 | | Date Posted: | 08.17.2026 14:41 | | Photo ID: | 9872859 | | VIRIN: | 260814-N-CF730-1023 | | Resolution: | 4519x3008 | | Size: | 2.16 MB | | Location: | SAN DIEGO, CALIFORNIA, US | | Web Views: | 1 | | Downloads: | 0 | This work, Naval Base San Diego presents Presidential Physical Fitness Awards [Image 4 of 4], by PO2 Ulrika Mendiola, identified by DVIDS, must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
Aug 17, 2026 · via dvidshub.net
This is an uncorrected proof. Figures Abstract Predicting the neural response to natural images in the visual cortex requires extracting relevant features from the images and relating those feature to the observed responses. In this work, we optimize the feature extraction in order to maximize the information shared between the image features and the neural response across voxels in a given region of interest (ROI) extracted from the BOLD signal measured by functional magnetic resonance imaging (fMRI). We adapt contrastive learning (CL) to fine-tune a convolutional neural network, which was pretrained for image classification, such that a mapping of a given image’s features are more similar to the corresponding fMRI response than to the responses to other images. We exploit the Natural Scenes Dataset as organized for the Algonauts Project, which contains the high-resolution fMRI responses of eight subjects to tens of thousands of naturalistic images. We show that CL fine-tuning creates feature extraction models that enable higher encoding accuracy in both early and higher visual ROIs as compared to the features from the pretrained network. Quantitatively, performance is similar to baseline approach that directly uses a regression loss at the output of the network to tune it for fMRI response encoding. We investigate inter-subject transfer of the CL fine-tuned models, including subjects from the Natural Object Dataset, another lower-resolution dataset with 9 subjects. We also pool subjects for fine-tuning, which further improves encoding performance in early ROIs. Finally, we examine the performance of the fine-tuned models on common image classification tasks, explore the landscape of ROI-specific models by applying dimensionality reduction on the Bhattacharya dissimilarity matrix created using the predictions on those tasks, show that these landscapes match those based on representational similarity analysis. Finally, we generate images via Stable Diffusion based on vector-space prompts created by aligning the
Aug 17, 2026 · via journals.plos.org
Machine Vision Insights from Industry Experts on Three Decades of Progress Key Highlights - Machine vision has evolved from proprietary, expensive components to standardized, affordable solutions driven by advances in CMOS sensors and imaging protocols. - Key technological milestones include the rise of CMOS cameras, LED lighting, SWIR imaging, and the integration of AI, transforming automated inspection and industrial applications. - Experts predict continued hardware commoditization, smarter systems with on-the-job learning, and broader adoption of SWIR imaging fueled by AI and emerging sensor technologies. Vision Systems Design is celebrating a major milestone in 2026: 30 years of covering the machine vision and imaging industry. VSD began as a spin-off of sister publication Laser Focus World. While machine vision may seem like a specialty market to some, it is in fact a robust, growing, multi-billion-dollar industry that clearly merits a publication dedicated exclusively to its coverage. Still, 30 years is a long time, and too often the present can seem a little slow—even static—until it becomes the past. A quick AI search will instantly generate a reasonably accurate timeline of machine vision’s evolution. In brief, research into image processing and pattern recognition—the foundations of applications such as automated inspection—began in the 1950s and 1960s. Industrial adoption accelerated in the 1980s and 1990s, while neural networks and deep learning expanded machine vision’s capabilities by 2010. Today, AI-powered platforms continue to push applications to new levels. Such an exercise is helpful, if for no other reason than it illustrates that the sheer power, not to mention convenience, of technology has advanced, almost unimaginably so, from just a few years ago. But a much more interesting exercise is to see the past, present, and future through the knowledgeable eyes, deep experience, and informed viewpoint of people who have seen the timeline unfold—first person and
Aug 17, 2026 · via vision-systems.com
It's not too long ago that buying something meant handing over cash, or at least a physical card.
But one company is looking to take digital payment a step further, introducing an option that allows you to make a purchase not with your device — but your face.
Paying "with a smile" is a fair way off being commonplace in Australia, and it would be an opt-in service. However, facial recognition becoming more commonplace across in our daily lives. So what's around the corner?
Guests:
- Lauren Perry, responsible technology policy specialist at the University of Technology Sydney
- Kirsten Drysdale, independent journalist and host of The Internet Reviewed
Credits
Image Details
Technology, Society, Data Privacy
Aug 17, 2026 · via abc.net.au
Supermarket giants trial facial recognition technology Updated . First published at Coles and Woolworths are exploring the use of facial recognition technology to use in its stores in a bid to crack down on retail crime. The potential use of the technology is the latest step the supermarket giants are taking to protect its staff and prevent theft in its stores. Coles told nine.com.au it had not conducted an outright trial of the technology, instead saying it had completed a “small, one-off, controlled proof-of-concept test of the technology.” “[It] did not use customer or team member information or data,” a Coles spokesperson said. “No decision has been made about the deployment of facial recognition technology. “We will always explore technology that will help us keep our team and customers safe.” Nine.com.au understands the test used volunteers, and did not use the data of any customers or staff. Despite previous reports, Woolworths has denied conducting a trial of the same technology across its New Zealand stores. It is understood the company conducted a small trial of facial recognition technology in New Zealand, but not at a store with customers or staff. Nine.com.au understands the company has no formal plans to roll out the technology in Australia. Facial recognition technology has proved controversial, with its use in Australian stores only being approved earlier this year after Westfarmers, owner of hardware chain Bunnings, won a legal battle that reversed an initial ruling that blocked its rollout. The company had used the technology between 2018 and 2021, and insisted the images of a “vast majority of people [were] processed and deleted in 0.00417 seconds”. Bunnings managing director Mike Schneider insisted the technology would only be used to protect its staff and customers. “Our intent in trialling this technology was to help protect people from
Aug 17, 2026 · via nine.com.au
Amazon Rekognition faces scrutiny in false arrest lawsuit Amazon Web Services (AWS) was added as a defendant in a federal lawsuit brought by a St. Louis, Missouri man who spent 17 months in jail after police used facial recognition on a poor quality image of a masked suspect and then built a case around the photo. Christopher Gatlin alleges in an amended complaint filed last Thursday that his arrest and prosecution resulted from poor police work, inadequate training, misconduct and a defective facial recognition system developed by Amazon. The new filing names AWS and identifies Amazon Rekognition as the technology involved in the identification that ultimately led police to Gatlin. The addition of Amazon significantly broadens this civil rights case that until now has focused largely on how St. Louis and county police used facial recognition and what they did after it identified Gatlin as a possible match. The case began with the December 7, 2020, assault of a MetroLink security guard at the St. Charles Rock Road station in north St. Louis County. The victim suffered a traumatic brain injury and repeatedly told police he could not remember the men who attacked him, according to allegations recounted in a federal court ruling. Detectives obtained surveillance video showing the attackers. One investigator eventually submitted an image of one of them to the St. Louis Mugshot Recognition Technology system. The federal court record describes the image as grainy, blurry, taken from a distance and from above the suspect’s face. A hood covered part of his forehead and a medical mask obscured another portion of his face. The system nevertheless returned possible candidates, including Gatlin. Before the facial recognition search, investigators had no information pointing to him as a suspect. The Washington Post subsequently found that the regional St. Louis facial recognition
Aug 17, 2026 · via biometricupdate.com
Meta smart glasses patent reignites facial recognition debate Meta’s latest smart glasses patent offers a glimpse of a future in which cameras do more than record what their wearer sees. They could identify who is there, interpret what is happening and determine which people or moments matter most to the wearer. The patent describes meaningful privacy and data-security controls, but it also raises questions Meta may need to answer if it wants users—and the people on the other side of the glasses—to trust the technology. Published August 13, US 2026/0238876 A1, “Smart Cameras Enabled by Assistant Systems,” describes an AI assistant combining cameras with capabilities including facial recognition, expression analysis, gaze and object recognition. The application is a continuation of a 2022 filing, which itself continues an application first filed in 2019. When the camera decides what matters The patent’s dinner-party example makes the concept tangible. A user wearing AR glasses is surrounded by several people. The assistant could use facial recognition to determine that one person is the user’s wife and assign her greater “interestingness.” The camera could then center on her while other people are excluded from the frame or blurred. Alternatively, facial-expression recognition could determine that two people laughing are more interesting subjects and focus the capture on them. The camera, in other words, is no longer simply capturing a scene. It is interpreting it. Privacy is built into the patent Importantly, Meta does not ignore privacy. Facial recognition and facial-expression recognition can be subject to privacy settings. The identity-resolution system can also respect restrictions preventing another person’s identity from being searchable. The patent describes controls allowing biometric information to be limited to specific purposes while restricting its use by other applications or sharing with third parties. Some assistant functions, including speech processing, reasoning and memory, can
Aug 17, 2026 · via biometricupdate.com