Right after Google I/O wrapped up in May, we shared the news that Google’s personal image search had just gotten a whole lot better. The tech giant claimed that you could now search through yours and your friends photos based on visual content, even if the photos themselves weren’t labeled or tagged.
At the time, all we knew was that the system used “computer vision and machine learning” to detect subjects like “flowers,” “food” or “car” and generate searchable tag data that makes your photos easier to find. Now, thanks to Google’s Research blog, we’re getting a bit more detail on the tech under the hood. Read more…
Google I/O brought with it a lot of exciting updates for Google+, not the least of which were a slew of automatic improvements to Google+ Photos including Auto Highlight, Auto Enhance and Auto Awesome. But the updates didn’t stop when I/O ended last Friday.
Today, Google’s Search blog announced that the company has started implementing some impressive technology that will allow you to search for your photos based on what they contain visually, even if there’s not a tag in sight. Read more…
With the prevalence of smartphones and the massive photo community that is Instagram, it’s no surprise that news outlets and journalists are more and more frequently turning to the service to source photos for major events. Unfortunately, Instagram’s search functionality is almost non-existent. That’s where the new open-source search tool QIS comes into play. Read more…
As people snap more and more digital photos, being able to organize those photos into useful sets is becoming increasingly important. Facial recognition algorithms are quickly becoming a standard feature in popular photo origination programs (e.g. iPhoto), but people-sorting is only the tip of the “semantic photo search” iceberg. Cloud photo service EverPix is one company that’s currently working to take photo recognition beyond faces. Sarah Perez of TechCrunch writes,
[...] the eventual goal for Everpix is to become the default way people choose to view and share photos. One development which could help it get there is the image analysis technology the company has been developing in-house. As people’s photo collections grow exponentially over the years, it’s something that will become more valuable in time. Using generalized semantic tagging techniques, Everpix is building algorithms that can identify what the photo is of – meaning, whether it’s a person, a night or day shot, a wide or close shot, a city scene, a nature photo, a photo of a baby, or a vehicle, or a photo of food, among many other things.
What’s important here is that the way they’ve built this to scale. After training the system on a minimal amount of photos, Everpix can then look for other photos in a user’s collection that match that signature without reprocessing the entire photo collection.
In the future, we’ll likely be able to search for photos with photos. Looking for a particular photo that you took at a popular tourist landmark? Just show the app a similar photo found online, and voilà, yours appears.
Cloud Photos Service Everpix Exits Beta With New Website & iPad App; Semantic Photo Search Coming Soon [TechCrunch]
Twitter sees hundreds or thousands of Tweets published every second, and many of these are photos of things happening real-time. Hashalbum is a new website that aims to help you browse this constant stream of images in real time by allowing you to do a simple search by hashtag, returning images that are found in Tweets containing that hashtag.
Hashalbum (via Lifehacker)