Is a picture worth a thousand clicks? You’ve heard of contextual ads triggered by keywords on a Web page. Now, get ready for contextual ads triggered by images on the page. Visual-shopping search engine Like.com is running ads on Facebook that appear to match objects in profile photos.

Notice the ad by Like.com in the lower left for aviator sunglasses in the screen shot shown here, sent to us by TechCrunch reader Luke Bearden? Yup, those look eerily similar to the aviator sunglasses Bearden is wearing in his Facebook photo. Well, at least we know that Like.com’s technology works. Or maybe it’s just a coincidence. (Can someone from Like/Riya let us know which one it is in comments?).

But if this indeed is Like’s image-matching engine at work, is it effective targeting? Bearden thought the ad was “creepy.” And, um, he obviously already owns a pair of aviator sunglasses.

He also obviously likes them enough to feature himself wearing a pair on his Facebook page. And maybe he lost those beloved glasses or they broke since the photo was taken. So I’d say the ad is both effective and creepy.

Would you click on it?

Update 6/2/08: Riya/Like founder Munjal Shah got back to us to let us know that, while his company’s technology could do this, in this case it was indeed a coincidence. He writes in an e-mail:

1) This ad is not contextually driven - it was just luck that the sunglasses matched - Facebook’s ad API doesn’t let you access the photo on the page for doing this kind of visual targeting.
2) We do have this visual targeting technology and use it on the Rockyou site (called Likesense), but it is not on Facebook at this time.
3) Other than that I liked the article - it is indicative of the direction we are heading…

(Screen shot courtesy of Luke Bearden).

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I can’t really say much about Tuyuan yet since it’s in Chinese and there isn’t much information (translated page here), but it certainly looks like they’re trying to tackle the facial recognition problem that has destroyed many a startup.

We’ve seen Riya (now focused on ecommerce via Like.com), Ookles (never launched), and Polar Rose (in private beta for nearly a year), among others. Most recently Tagcow came on the scene, but it turns out it uses humans to tag photos, which tends to produce bad data.

Will Tuyuan be any different? We have no idea yet. But we’re contacting them to find out. More soon. Thanks for the tip, Orli.

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Most people have thousands of digital photos sitting on their hard drive. And the vast majority of those photos aren’t tagged or searchable. Want to find the 300 pictures of your youngest son amongst 10,000 others? It’s not going to happen. Unless you’ve been diligently tagging and categorizing those photos over the years, and who does that?

The problem is obvious. The solution, not so much. A trail of failed startups have tried to tackle the problem with a fairly serious application of technology, including: Riya (now focused on ecommerce via Like.com), Ookles (never launched), and Polar Rose (in private beta for nearly a year), among others.

And now suddenly TagCow appears, which allows users to upload photos and have them tagged within a few minutes. The technology appears to be “magic,” meaning there’s no explanation of it.

If there’s a mountain in the photo, it’s tagged. A dog? yep. A yellow cup? Absolutely. It does people, too. Upload an image of a person and say who it is, and all other images you upload will be tagged with that person, too. The service also integrates with Flickr and will auto tag the photos you have on the service.

Thomas Hawk, the CEO of photo site Zooomr, tried the service and declared it “really, really cool,” although he wonders how it works.

The answer is, humans do it. I note that the TagCow site is careful not to say anything about the tagging process, and never use the word “automated” or anything else that would suggests computers are doing the work. Munjal Shah, the founder of Riya/Like, agreed, noting that it recognized a witch in Thomas’ photo - he says this just isn’t something a computer can do today.

I haven’t confirmed this yet. I’ve emailed the company for a description of how the service works but have yet to hear back. Until we do, I’m betting that humans are the taggers. Note that Google has effectively thrown in the towel and uses humans for this kind of work, too.

TagCow appears to be offering the service for free, so the cost side of the business may be a problem for them down the road. And the business is definitely a little sketchy. Worried about the privacy of your data? Just don’t click on their Privacy Policy or Terms of Use: “Privacy policy is TBD.” and “Legal stuff TBD.” Not exactly a way to build confidence.

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Last November, Munjal Shah made a fairly tough decision and did an about face on his startup, Riya. Instead of continuing to focus on Riya’s existing product - facial recognition and tagging of photos - the company took its core technology and launched an image search engine called Like.com.

Unlike other image search engines, Like.com uses photos as the query, returning similar images as the results. The company focused on ecommerce, particularly fashion items like handbags, watches, shoes, etc.

Fast forward to nearly a year later. The company is generating real revenue from sales on the site - Current gross merchandise sales are running at about $12 million per year (Like.com gets a small percentage of that as an affiliate fee in revenue). 1 million or so unique visitors come to the site each month.

This weekend photo widget startup RockYou started to integrate Like.com results into slide shows shown on the RockYou site (example). For now, results are limited to showing shirts on sale that are similar to the ones being worn by people in the photographs. Viewers can click through and purchase a shirt that look similar to the one their friend is wearing in the photos.

So far, so good. Shah says they are seeing an $0.80 CPM on slide show pages and sharing the revenue wtih RockYou. Other partnerships are ready to roll out.

Slide shows with Like.com results are only being shown on RockYou.com currently - due to issues with advertising on social networks (particularly MySpace), they are not included in the embeddable widgets. It’ll take a whole new round of negotiations before we start seeing them there, too.

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Xcavator.net is a stock photo search portal based on visual search technology.

Xcavator.net provides natural and intuitive interactive search for stock photography providing buyers with a browsing experience based on both visual content and keywords. The key to the visual search capabilities is the portal’s color and image search engines, powered by CogniSign Intelligent Image Recognition Technology.

In laymen’s terms, Xcavator.net offers three types of interrelated search options. Tradition search delivers photos based on tagged keywords and is much the same as others in the stock photography market. Where Xcavator.net gets interesting is in color and image search. Xcavator.net allows color search matching, for example if a stock photograph was needed that matched a brochure or web site in terms of colors, users are able to refine the photo search to those colors by utilizing a color chart or by inserting the exact hexadecimal color into a box. Image search provides similar photos based on a user uploaded image or via a drag and drop of images found in an initial search.

Xcavator.net competes with other visual search sites including Riya, Pixsy and PicSearch. Xcavator isn’t necessarily better than any of their competitors, but different. The color and related search capabilities don’t have the same level of user enjoyment as Riya’s search features do, yet Xcavator.net’s features feel more practical and are definitely more finely targeted at niche stock photo search.

Xcavator.net recently signed a deal with iStockphoto that delivers 1.8 Million images from 38,000 contributors into the Xcavator.net search database. The site comes out of Beta on July 2.

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Silicon Valley startup Riya, currently a photo search company focusing on facial recognition, is making a significant strategic and product shift this morning. Riya will continue as is, but the company is leveraging the core technology to launch a new image search engine called Like.com (see our previous coverage of Riya here).

Like.com is image search. There are lots of other image search engines on the web today. But all of them only take queries as text, and compare those text queries to the meta data attached to an image file. This data is notoriously thin, and companies like Google are resorting to using human labor to attempt to add descriptive keywords to images stored on their servers. Even specialty image search engines like Pixsy have fairly thin meta data for images. And all of the existing search engines allow only text for search queries.

The Like.com engine takes both text and images as queries, something no one else does. To return results based on an image query, Like.com compares a “visual signature” for the query image to possible results. The visual signature is simply a mathematical representatioin of the image using 10,000 variables. If enough variables are identical, Like.com decides the images are similar.

What this means - If you see an image on the web, like a watch that Paris Hilton is wearing in the picture to the left, and use it as an image query, Like.com will return results showing watches that look very similar.

If you enter a text query, like “brown boots pointed toe,” Like.com will convert that query into variables in the visual signature and look for related image results. See screen shot below for the results from this query.

The site launching today returns results only for shoes, jewelry, hand bags and clothing. The service will expand over time to include other categories, but these initial categories represent a very large portion of consumer discretionary spending in the real world. With each result Like.com will also present a link to purchase the item, and their hope is to generate revenue from subsequent purchases.

A key feature that Like.com will be launching in the next month or so is an image uploader and a toolbar. Upload an image to Like.com to see similar results. Or, simply use the toolbar to use any image found on the web as a search query. Either way, Like.com will return results for similar items.

Robert Scoble at Podtech interviewed Riya CEO Munjal Shah on video in preparation for the launch. See the interview here, and a product demo here.

On a side note, Munjal has written a series of fifteen blog posts talking about his experience as a startup CEO. This is a very useful resource for new entrepreneurs. And given the length of this series, I wouldn’t be surprised to see Munjal publish this as a book at some point as well.

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Photo search and facial recognition site Riya (a TechCrunch sponsor) had a million photos uploaded in the first two days after launch and seven million photos uploaded in the first seven weeks. For details on the core service, see this post and listen this podcast interview with Riya founder and CEO Munjal Shah.

Next up - Riya 2.0.

It’s still a few months away from launching, but I spoke with Munjal this evening and he gave me an overview of what to expect from the service. It will be a “visual search engine” - give Riya an image and it will return image results that are similar from across the web. They’ve already begun crawling the web for images, a process that will take many months.

When it’s ready, users will be able to search on an image (the easiest way will be via a browser plugin to search right from the page containing the images). See a rug on ebay that has a pattern you like? See other rugs from across the web containing similar patterns. Riya will make money if the result you click on is from another ecommerce company - Riya pockets the referral fee.

Dating is another (if slightly creepy) use for the new Visual Search engine. See someone’s picture on MySpace that you like? Search on their photo to find single people who look similar and who have profiles up on match.com or other dating sites. Again, Riya makes a referral fee by moving the traffic along.

The infrastructure needed to crawl the web is substantial, says Munjal, and they’ve been working to build out a new data center over the last few months.

I believe Dan Farber was the first to write about Riya 2.0. More on Munjal’s blog, and he briefed Matt Marshall and Laurie Sullivan as well.

In other Riya news, a Mac version of their uploader was released tonight.

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Photo search and facial recognition site Riya is now about two months old (see here for our past Riya posts). Founder and CEO Munjal Shah is in the process of memorializing the highs and lows of the launch process, and this is must-read stuff for entrepreneurs looking to launch a company down the road. I may update my “Don’t Blow Your Beta” post based on some of his advice. Part 1 is up now, look for further installments on the blog. Bookmark this stuff, it’s free consulting.

Disclosure: This is the first time I’ve written about a direct advertiser on TechCrunch - Riya became a sponsor a couple of weeks ago.

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Photo search and facial recognition startup Riya launched on March 21 and had a million photos uploaded in the first two days. We interview Riya CEO Munjal Shah and Marketing Director Tara Hunt on TalkCrunch to understand what Riya’s plans are in the near future. Check it out over on TalkCrunch.

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Tara Hunt, Riya’s chief blogger, says on her personal blog that they’ve had a million photos uploaded just two days after launching. Wow, that’s a lot of pictures. Congratulations (again) Riya.

More on what Riya is all about here.

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