Porn companies adopt facial-recognition technology, encourage Instagram photos Two porn companies are courting web surfers to upload photos they find online to the companies' free facial-recognition, face-matching database services. With SexFaceFinder.com and Naughty America's "Face" anyone can upload an image and have the services match it with images and faces in image databases. SexFaceFinder positions its service as a way for users to find a performer that looks like s specific person. Or to find performers that look like the user's favorite type of model, in an effort to engage the user with a service that closes the marketing gap between a user and their fantasy. Another company, Naughty America, openly solicits users to upload images of girls found on Instagram and other internet destinations in an effort to find the photo's subjects in porn - or find celebrity look-alikes, girlfriend and ex-girlfriend look-alikes, or similar/specific porn performers. According to Naughty America's press, it attempts to match user-uploaded images to its own porn database.
People Search Products & Services The Internet is a really fantastic place where access to information is nearly unlimited â€“ that is, until we try to locate information about someone. Information about ourselves and the people we know (or want to get to know) is available through public records, but narrowing down the public records can be downright impossible. PeopleSmart solved this problem by providing the Internetâ€™s next generation people search engine. What does this mean? Apple Patent Describes a More Secure Face-Recognition System An Apple face-recognition patent shows how 3-D imaging could provide for better system security. Images: Free Patents Online A new Apple patent application concerning face-recognition technology suggests an interesting security update for iOS. And that could be just the beginning of what the technology might enable. The patent, “3D Object Recognition,” describes a novel way to generate 3-D models using 2-D images.
LFW : Results Introduction LFW provides information for supervised learning under two different training paradigms: image-restricted and unrestricted. Under the image-restricted setting, only binary "matched" or "mismatched" labels are given, for pairs of images. Face recognition software can grab personal information, social security numbers It is possible to identify strangers and gain their personal information - perhaps even their social security numbers - by using face recognition software and social media profiles, according to a new study by Carnegie Mellon University's Alessandro Acquisti and his research team. The results of the study will be presented 4 August at Black Hat, a security conference in Las Vegas. "A person's face is the veritable link between her offline and online identities," said Acquisti, associate professor of information technology and public policy at the Heinz College and a Carnegie Mellon CyLab researcher. "When we share tagged photos of ourselves online, it becomes possible for others to link our face to our names in situations where we would normally expect anonymity."
Free People Search - topics.info.com Those looking for out-of-touch friends and family often use a free people search. ©Jupiter Images, 2009 Using a free people search site is usually quick and simple. Free People Search Google's Artificial Brain Learns to Find Cat Videos By Liat Clark, Wired UK When computer scientists at Google’s mysterious X lab built a neural network of 16,000 computer processors with one billion connections and let it browse YouTube, it did what many web users might do — it began to look for cats. [partner id=”wireduk”] The “brain” simulation was exposed to 10 million randomly selected YouTube video thumbnails over the course of three days and, after being presented with a list of 20,000 different items, it began to recognize pictures of cats using a “deep learning” algorithm. This was despite being fed no information on distinguishing features that might help identify one. Picking up on the most commonly occurring images featured on YouTube, the system achieved 81.7 percent accuracy in detecting human faces, 76.7 percent accuracy when identifying human body parts and 74.8 percent accuracy when identifying cats. “The network is sensitive to high-level concepts such as cat faces and human bodies.
LFW Face Database : Main Welcome to Labeled Faces in the Wild, a database of face photographs designed for studying the problem of unconstrained face recognition. The data set contains more than 13,000 images of faces collected from the web. Each face has been labeled with the name of the person pictured. 1680 of the people pictured have two or more distinct photos in the data set. The only constraint on these faces is that they were detected by the Viola-Jones face detector. More details can be found in the technical report below. Developments in Facial Recognition Eventually, it will work. You'll be able to wear a camera that will automatically recognize someone walking towards you, and a earpiece that will relay who that person is and maybe something about him. None of the technologies required to make this work are hard; it's just a matter of getting the error rate down low enough for it to be a useful system.
How Google is teaching computers to see Google’s Hangouts recognize people, even if they are just a photo. Google is attempting to teach computers to recognize human faces without telling the computing algorithms which faces are human. It’s a machine-learning problem made for this era of unstructured data and easy access to large compute clusters. It could help the search giant make huge strides in building the next big opportunity in tech, enabling computers to “see.” facial tagging A 1.3 Gigapixel image featuring around 70,000 people is lined up to create a world record for the most tagged online image ever. It has been created by stitching together 36 photographs of the crowd at Glastonbury Festival in the UK last week, while they were watching the England vs Slovenia World Cup match. The image is being used as part of a promotional site for mobile phone network Orange. The Glastotag site is aiming for the record of ‘Most people tagged in an online photo’. Thanks to the sheer size of the photograph it’s possible to zoom incredibly far in, allowing you to make out indivdual members of the crowd, even those right at the back. Tagging is done via Facebook integration and at the time of writing nearly 1500 people had already been tagged in the image.
Identifying faces in a crowd in real-time Published 2 September 2010 U.K. company develops a face recognition technology that can recognize individual faces in a crowd — and do so in seconds, even when they are moving, at a wide angle, or in poor light; the system captures and analyzes images and compares them to a database, and alerts security personnel if a match is made A new type of infrared security camera is being used to identify individual faces in real time. The CheckPoint.S system from Guildford, Surrey, U.K.
Facebook's Mobile Strategy is Flawed, Eye-Tracking Study Indicates Fresh off of a lackluster second-quarter earnings release and new lows in its share price, Facebook was dealt more bad news on Friday when EyeTrackShop, a firm that measures audience attention, released a study suggesting that Facebook’s business model may be broken. The culprit? The same mobile ads that CEO Mark Zuckerberg and COO Sheryl Sandberg lauded when they spoke with analysts Thursday afternoon. EyeTrackShop analyzes webcam imagery to track the eye movements of individual audience members while they attend to onscreen content. The firm's study examined audience attention to ads displayed by Facebook on its website as well as on its apps for iPhone and iPad. While adds displayed in iPad apps generally did better than those on the Website, ads displayed on the iPhone performed poorly.