Scientists at the Fudan University and Changchun Institute of Optics, Fine Mechanics and Physics in China have developed a 500MP cloud-connected 'super camera' that can reportedly pick out facial details of an individual person among thousands in a crowded stadium. The new tech is raising serious concerns about privacy and government monitoring.
The team at photo community and marketplace EyeEm just released something really cool. Announced this morning, their new standalone iOS app "The Roll" is basically a much more powerful, intelligent replacement for Apple's Camera Roll.
Clarifai, a NYC-based startup that's developing state-of-the-art image recognition software, has launched a new free photo app on iOS. It's called Forevery, and it's a new AI-powered app that helps you organize, discover, and share photos on your phone.
With over a trillion photos created every year now, one feature that could help people make sense of their massive photo collections could be object recognition and automatic tagging. If your camera and photo management software can figure out what's in your shots, it'll make searching through old photos much more easy and intuitive.
Companies and researchers are working hard on pushing this field forward. Photo sharing services are already adding auto-tagging to their systems -- Flickr and Google had to work out some early "racist" bugs -- and now we're getting a glimpse of what the technology could look like live, in cameras.
A new patent filed by Facebook suggests that the social networking giant is working on giving user cameras a unique digital fingerprint. Looking for ways to identify fraudulent accounts and evermore establish what connections you may have with others, the new technology means that your future photographs will be tracked at levels previously unimaginable. For photographers, however, it may be an excellent way to prove that you truly own an image.
One of the emerging trends in the world of photography is the idea of automated recognition and tagging of things found in photographs. Flickr can now suggest autotags for your photos, and Google's new Photos service lets you search through your unlabeled photos using advanced image recognition.
The same technologies are coming for real-time camera features as well. Qualcomm is working on a system called SceneDetect that lets cameras recognize what they're looking at in real time.
Three year old children can make sense of what they see in photos and describe them to us, but even the most advanced computers have historically had difficulties with that same task. That's quickly changing though, as computer scientists are developing powerful new ways to have computers identify what a photograph is showing.
The video above is a new TED talk given by Fei-Fei Li, a Stanford professor who's one of the world's leading experts on computer vision. She talks about her revolutionary ImageNet project that has changed how computers "see."
It might not be the most useful website ever designed, but Flickr's new Park or Bird microsite serves a purpose: namely, it's the Flickr Vision team's response to a challenge by the popular webcomic XKCD.
When a beta version of Apple's iOS software is released, you can bet developers are sifting through the code like mad to see if any new features have been added to the mobile operating system.
It would appear as if hidden in the code for iOS 7 beta 2 are camera-oriented features for use by developers. One feature apparently detects smiling in photos, the other detects blinking. These detectors may hint at features coming to the iPhone, iPod, and iPad cameras in the future.
In this day and age, you're likely to have a hard time walking down the street and not seeing a camera somewhere. If it isn't held by the shutter-happy tourist in short shorts, it's the CCTV camera mounted at the entrance of the local subway station.
How does one maintain anonymity? Staying in? No! You put on fabulous privacy-protecting glasses under development by Japan's National Institute of Informatics.
Cameras these days are smart enough to recognize the faces found inside photographs and label them with names. What if the same kind of recognition could be done for the locations of photographs? What if, instead of using satellite geodata, the camera could simply recognize where it is by the contents of the photographs?
That's what research being done at Carnegie Mellon University and INRIA/Ecole Normale Supérieure in Paris may one day lead to. A group of researchers have created a computer program that can identify the distinctive architectural elements of major cities by processing street-level photos.
Facial recognition technology has become ubiquitous in recent years, being found in everything from the latest compact camera to websites like Facebook. The same may soon be said about location recognition.
Google has acquired UK-based mobile photo search startup …