Researchers design inconspicuous eyeglasses that trick facial recognition systems

Researchers at Carnegie Mellon University and the University of North Carolina at Chapel Hill have developed a method of creating inconspicuous eyeglasses that can be used to thwart identification by facial recognition algorithms, according to their published findings (PDF). The researchers developed five pairs of “universal” glasses that “facilitate misclassification” through an adversarial generative nets (AGN) method, which involves using neural networks to produce designs with different colors and textures for glasses that can either evade correct identification or impersonate

CMU creates new AI initiative to attract more startups and investors

Carnegie Mellon University’s new CMU AI initiative will bring together its various areas of artificial intelligence research under one large group and potentially attract more startups and investors to the university and region, according to a report by Pittsburgh Post-Gazette. “There are multiple parts to [AI]. One of the strengths of Carnegie Mellon is that we are experts in all of those parts,” said Andrew Moore, dean of CMU’s School of Computer Science. “As we have grown, we have focused

Researchers improve method to detect faces in a crowd from small images

Researchers at Carnegie Mellon University have developed a method for detecting multiple faces in a crowd from small images with a greatly reduced error factor, according to a report in The Tartan. The process described in the Finding Tiny Faces report involves focusing a computer on specific pixels within a “massively-large receptor field,” in which 99 percent of the template examined is beyond the object of interest, and which provides the context to detect small objects. While most recognition approaches

Facebook picks up facial recognition startup FacioMetrics

Facebook has acquired facial recognition startup FacioMetrics for an undisclosed amount. Using facial image analysis to determine emotions, FacioMetrics is aimed at a range of sectors including gaming, healthcare, augmented reality, and robotics. FacioMetrics founder and CEO Fernando De la Torre said the company’s facial image analysis technology offers several applications including augmented/virtual reality, animation, and audience reaction measurement. According to a report by ZDNet, the technology was born out of Carnegie Mellon University regarding computer vision and machine learning

CMU researchers develop glasses that dupe facial recognition

Researchers from Carnegie Mellon University have developed a special pair of eyeglass frames in which it can enable commercial-grade facial recognition software to identify the wrong individual with up to 100% success rate, according to a report by In a research paper presented at a security conference last week, CMU researchers demonstrated how they could dupe AI facial recognition systems into misidentifying faces. In other words, the glasses were able to make an individual who is captured on camera

Biometrics and smart cards, privacy, patents and mobile identity credentialing trending this week

Here is a recap of the most popular biometrics industry news that appeared on this past week. Biometric smart cards A consumer survey of credit card users in the United States found that 80% of those questioned are concerned about credit card and identity fraud and that 67% of those users would be willing to pay for a biometrics secured credit card that has a built-in fingerprint reader for protection. NEXT Biometrics introduced the new generation of fingerprint sensors

Carnegie Mellon wins Navy contract to develop improved biometric surveillance

Carnegie Mellon University has won an $8.9M Navy contract to research and develop new algorithms for the U.S. Navy’s aerial and biometric surveillance efforts. The one-year contract focuses on “basic and applied research of unconstrained resolution, occlusion, pose, and aging-tracking, surveillance and identification (UROPA-TSI) in support of the Special Surveillance Program,” according to the Department of Defense contract announcement. The research will provide next-generation algorithms and cutting edge fundamental research to solve difficult scientific problems, such as low-resolution, occlusion, pose,