"Image understanding (IU) is the research area concerned with the design and experimentation of computer systems that integrate explicit models of a visual problem domain with one or more methods for extracting features from images and one or more methods for matching features with models using a control structure. Given a goal, or a reason for looking at a particular scene, these systems produce descriptions of both the images and the world scenes that the images represent."
– Image Understanding, by J.K. Tsotos. In Encyclopedia of Artificial Intelligence. Stuart C. Shapiro, editor. 1987. New York: John Wiley & Sons.
The front of the device features a cutout at the top of the new OLED Super Retina display housing a new True Depth camera system for the Face ID facial recognition system and for taking selfies with Apple's Portrait Mode. The iPhone X will have Apple's latest processor, the A11 Bionic with an integrated Neural Engine for face recognition, which now has six cores – up from last year's A10 with four cores. Apple also unveiled new animated emoji characters it calls "animoji", which allow users to map facial expressions on to little characters, such as a robot, fox, unicorn, or anthropomorphised poo using the iPhone X's facial recognition system. The iPhone 8 and 8 Plus both have Apple's new A11 Bionic chip, but without the Neural Engine of that fitted to the iPhone X, have improved screens with the company's True Tone feature, improved speakers and keep its current form with a home button with Touch ID 2 fingerprint scanner, but lack facial recognition and an all-screen design.
Amarjot Singh at the University of Cambridge and his colleagues trained a machine learning algorithm to locate 14 key facial points. The researchers then hand-labelled 2000 photos of people wearing hats, glasses, scarves and fake beards to indicate the location of those same key points, even if they couldn't be seen. The system accurately identified people a wearing scarf 77 per cent of the time – a cap and scarf 69 per cent of the time and a cap, scarf and glasses 55 per cent of the time. Last year, a team of researchers from Carnegie Mellon University found they could trick face recognition software by wearing specially designed glasses.
We first created a database of lensless images of handwritten digits. Then, we trained a ML algorithm on this dataset. Finally, we demonstrated that the trained ML algorithm is able to classify the digits with accuracy as high as 99% for 2 digits. Our approach clearly demonstrates the potential for non-human cameras in machine-based decision-making scenarios.
For this, we need to create an IAM role that grants our function the rights to access the objects from Amazon S3, initiate the IndexFaces function of Amazon Rekognition, and create multiple entries within our Amazon DynamoDB key-value store for a mapping between the FaceId and the person's full name. To create the service role for Lambda, we need two JSON files that describe the trust and access policies: trust-policy.json For the access policy, ensure you replace aws-region, account-id, and the actual name of the resources (e.g., bucket-name and family_collection) with the name of the resources in your environment. The reason I'm adding multiple references for a single person to the image collection is because adding multiple reference images per person greatly enhances the potential match rate for a person. I also provided guidance on how to integrate Amazon Rekognition with other AWS services such as AWS Lambda, Amazon S3, Amazon DynamoDB, or IAM.
The phone will be able to use facial recognition technology to see its owner in just a few hundred miliseconds, according to new leaks from both The Korea Herald and Bloomberg. Rumours about Apple's facial recognition have swirled for months, and seemed to be confirmed by leaked iPhone code that made its way onto the internet. Together, the improvements to those facial recognition features mean they will probably be among the top ways of selling the phones at their launch next month. Other companies including Samsung have brought face and eye recognition to their phones in the past.
Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classific... more
Familiarity alters face recognition: Familiar faces are recognized more accurately than unfamiliar ones and under difficult viewing conditions when unfamiliar face recognition fails. Using whole-brain functional magnetic resonance imaging, we found that personally familiar faces engage the macaque face-processing network more than unfamiliar faces. Familiar faces also recruited two hitherto unknown face areas at anatomically conserved locations within the perirhinal cortex and the temporal pole. These two areas, but not the core face-processing network, responded to familiar faces emerging from a blur with a characteristic nonlinear surge, akin to the abruptness of familiar face recognition.
The technology is expected to replace the Apple TouchID fingerprint sensor which has been there in iPhones since iPhone 5S. It seems, just like the ARKit, Apple might provide a BiometricKit to developers for creating more applications for the face recognition sensor inside the device's front camera -- it could be used for more than just unlocking the device. Chances are that the upcoming device features facial recognition, but without a TouchID sensor. Read: iPhone 8's Facial Recognition Feature To Be Used For Apple Pay Payments According to some reports, TouchID could be moved to the edge of the handset alongside the power button, however, this hasn't been done before and the possibility of Apple altering the form factor of its device to accommodate a TouchID sensor doesn't seem very high.