Two such "divining" projects include CoPhIR (Content-based Photo Image Retrieval) Test-Collection and IBM's MUFIN (Multi-Feature Indexing Network). These projects tie into SAPIR's back end by extracting data from the Flickr archive and indexing features such as scalable color, color structure, color layout, shape edges and texture.

As shown in the video of Madrid's Plaza de España, SAPIR identifies matching media in the same way that humans derive intrinsic value from visual and sensory clues. Users can also choose to combine search terms with additional text to further drill down in search results. As is the case with regular search, if you already know the city where your image was taken, you're one step closer to finding your result. Additionally, SAPIR also has the ability to index sound and video files.

While the catalogue of media is still very limited, theoretically we may one day be able to search for almost anything using this technique. If Ashton Kutcher wears a pair of sunglasses we like, we can scan the image and search for the storefronts stocking them. If we're looking for the name of a town square, we can find it in the tags of similar images. And finally, if we're looking to self-diagnose we can compare photos of ourselves against jaundice or malaria patients.

The advantage of this tool is that we may one day have a chance to collect up the disparate bits in the digital ether and identify them as useful points of information. To test SAPIR in its early research stage, visit the homepage. You may also want to test out MUFIN to compare results.

Google is not the first company to add face recognition to online photo albums. Riya, when it first launched, made face recognition its central feature, but Riya's implementation, while interesting, made too many mistakes in the face recognition to be successful. Most users quickly abandoned the site after the early hype and Riya was forced to change its business model. To be successful, Google's face recognition will have to be a lot more precise than Riya's algorithms.

Picasa Update

The updates to the Picasa desktop software are interesting, but not revolutionary. Two features stand out, though. The movie maker mode will allow users to create videos of their slide shows and upload them to YouTube. The online synchronization feature will keep galleries in the desktop client in synch with the web albums. Sadly, though, this synchronization only seems to work from PC to web and not vice versa, making this potentially great feature just a bit less useful.

Competition

It's good to see that Google is showing some drive to innovate in the online photo album market. Flickr, as Stephen Shankland points out, has been slow to add new features, and Picasa itself has not exactly been the most exciting place to store pictures. If Google can make the face recognition work, it will have at least one great feature that will set it apart from its competition.

Windows Only

When Microsoft first publicly showed a demo of Photosynth in 2006, it almost looked too good to be true. Now, getting started with it couldn't be easier - as long as you have a Windows machine - there is no Mac version available yet. You first have to install both a browser plug-in and a desktop application (all done through just one installer). The installation was as standard as Windows installations get and finished in less than a minute. We tested the plugin in both Firefox 3 and Internet Explorer 7 without any problems.

One interesting aspect of the uploader is that you can choose a license for your creation. You can either choose a Creative Commons license, put the pictures in public domain, or mark it as 'All Rights Reserved.'

Desktop App

The desktop application does most of the heavy lifting for creating the 'synths' and seemed to make good use of all available cores. You only have to pick your photos, give your collection and name and click 'Synth.' After it has finished, it will create a score telling you how 'synthy' your photo collection was. Obviously, your photos need to have common areas for Photosynth to be able to stitch them together. While Photosynth does a great job making these connections, it can't work magic and our first attempts with relatively unconnected images were futile.

The more pictures you have, the longer the process of creating your synths takes, of course, and depending on your connection, the upload to Microsoft's servers can also take quite a while. In the end, though, your patience will be greatly rewarded.

Online Viewer

The online viewer is quite intuitive and allows you to zoom in and out, move around the picture and also go through the pictures in a 3D slide show mode. One nice feature is that you can also go full screen, which is really the best way to showcase your photos.

You can also embed a copy of your synth on any website and email a link to your friends.

The animation in Photosynth is astonishingly smooth and our screenshots really can't do it justice. If you haven't seen it yet, you should watch Microsoft's demo of Photosynth at TED2007, which will give you a good impression of what the final product looks like.

Different Way of Shooting

It really takes a different approach to shooting pictures to make the most out of Photosynth. If you often stitch together photos, you are probably already used to this, but Photosynth also gives you more freedom, as you can zoom in and out, or walk around an object and still have Photosynth recognize the common areas.

In our tests, Photosynth performed flawlessly, but we would recommend that you have a set of at least 10 to 20 photos to create an interesting 'synth' and the more photos you have, the more interesting it will be.

Caveats

A couple of caveats:

• All synths are public - there are no privacy controls!
• Photosynth only runs on Vista and XP so far.

Verdict

Even though we only had a short time to test Photosynth, it has already changed the way we think about taking pictures. Suddenly, you can do so much more with your photos. But besides the cool factor, we can also see a lot of other interesting applications for Photosynth. A realtor, for example, could use it to create a more immersive virtual tour of a house.

If you already have Photosynth installed already, you can see a 3D view of Venice below - otherwise, clicking on the image will take you directly to the installer.

From the labs of the makers of the image search engine TinEye comes an extraordinary product. The Multicolr Search Lab allows users to select up to 10 colors that they would like the images they are searching for to contain. To make a color more prominent in the image search results simply select that color several times from the provided color palette. As you pick and choose your colors the search results will automatically refresh with images that represent your new color selections.

So far, the Multicolr Search lab is available for Flickr and Alamy Stock Photography. However, not every Flickr image will be searched. According to the site, they extract the colors "from 3 million "interesting" Flickr images. Using our visual similarity technology you can navigate the collection by colour."

Unique Image Search Engines

In addition to the Multicolr Search Lab, I'd also recommend checking out the BYO Image Search Lab from Idée. The BYO or 'Bring Your Own' Image Search Lab allows you to upload an image or choose one that's available on the web and find images from Alamy with similarities such as color tones.

Both search engines are great and unique tools to make the best of. I didn't have any problems getting great matches to the colors and images that I provided. Another bonus is the use of the Flickr "Interesting" set to ensure the best quality photo results. These are two great services that we'll be sure to keep an eye on.

Nicholas Carr blogged about Gwap a couple of days after its launch, noting that "one thing the Internet enables, which wasn't possible before, at least not on anywhere near the same scale, is the transfer of human intelligence into machine intelligence." In Gwap, which stands for "Games With a Purpose," that transfer of intelligence is done by getting people to do the routine chores that computers don't know how to do - chores like tagging photos, describing songs, and outlining objects, as well as transferring a good bit of human common sense to the machine. The trick to getting people to do these things is to make the work fun. Hence the games.

The creator of these games is Luis von Ahn, winner of a 2006 MacArthur Foundation "genius grant" and a pioneer in the field of human computation. Ahn is most notable for helping to develop CAPTCHAs (Completely Automated Public Turing Test to Tell Computers and Humans Apart), those somewhat annoying but rather effective distorted letter puzzles used millions of times each day. Last year, he also introduced the "reCAPTCHA," where CAPTCHAs were used to gain access to a web site while also helping digitize old books.

Gwap homepage

The Games

Gwap currently features five games, one of which is an old classic called the ESP Game. In the ESP game, two players view the same image and try to guess words that the other player would use to describe it. Google licensed this technology and launched Google Image Labeler to help improve the quality of their image search results.

• Matchin, a game in which players judge which of two images is more appealing, is designed to eventually enable image searches to rank images based on which ones look the best.
• Tag a Tune, in which players describe songs so that computers can search for music other than by title - such as happy songs or love songs.
• Verbosity, a test of common sense knowledge that will amass facts for use by artificial intelligence programs.
• Squigl, a game in which players trace the outlines of objects in photographs to help teach computers to more readily recognize objects.

According to the Carnegie Mellon announcement, von Ahn plans to add a lot of games to the site, saying "we have three more that we'll be launching in the coming months." He hopes that by having all the games on the same site it will encourage players to try several different ones. Players also have a single sign-on and password, Top Player rankings, and online chats, said von Ahn.

The Human Processor

In his whitepaper entitled "Invisible Computing," von Ahn compared game design to to algorithm creation, saying:

"...it must be proven correct, its efficiency can be analyzed, a more efficient version can supersede a less efficient one, and so on. Instead of using a silicon processor, these "algorithms" run on a processor consisting of ordinary humans interacting with computers over the Internet."

In other words, we're the processor. The machine is us.

This concept isn't entirely new - Amazon's Mechanical Turk, for example, pays people to contribute their time to work on small, simple tasks called "Human Intelligence Tasks," or HITs. However, unlike HITs, which can sometimes be boring or tedious, the games on Gawp are actually fun - and they don't feel like work.

Some believe that human powered processing is the next big wave for computing. You could argue that Mahalo, the human-powered search engine is an example of this. (Though others call it a human-powered link farm.) Perhaps a better example is ChaCha, the mobile Q&A service that uses human guides to respond to questions called or texted in from your cell phone. We've also covered other human-powered services on RWW in the past, like the Galaxy Zoo and Stardust@Home project, among other (our coverage here). Many of these efforts have tried to incorporate an element of "fun" into what is actually work.

Whether Gwap will actually gain momentum and get a large number of people involved is yet to be seen, but it is definitely has potential to help teach computers the things they can't do for themselves....yet.

So a search technology that actually looked at a picture and could understand what was in it -- or at least match like images -- would have a large number of practical applications. Picollator's online demo is based on software of the same name from parent company Recogmission. The demo allows users to upload an image of a face to the site, and then attempts to match it to similar images it has gathered from around the web.

One of the main issues we've noticed with most of these facial recognition products is their inability to deal with my facial hear -- sometimes even thinking that my dark beard is really an indication of my skin tone. So I was excited when Picollator matched me to a picture of Russell Crowe. I don't really look like Crowe, but believe it or not, people actually used to tell me I did back in college.

Unfortunately for Picollator, subsequent tests with different images were less successful. It had trouble dealing with an older picture of mine (though to be fair it had less face and more body), and also didn't respond well to a black and white picture. And if their software really is accurate, I am dating a girl who basically looks like any celebrity that smiles.

What that means is basically that image recognition software still has a long way to go. Certainly, these technologies will improve over time, but for now, the flawed approach of text based image search from Google, Yahoo! and the other big search engines is probably the best way to go.