I’ve been wondering why Google doesn’t document these specialized type image searches.

I do think Google will start doing more with OCR at some point in the future. It does seem to make sense for Google to try out games like this as well, since they try to solve problems that humans can solve much more easily than computers.

&imgtype=face

and all that will be returned in your search are faces. You can perform similar queries with:

&imgtype=lineart and &imgtype=body etc.

While this is nothing new it is still an interesting field when looking at the broader picture of just how Google plans to categorise the world’s images.

OCR is going to play a big part, and I think “games” such as this, where Google relies upon human judgement to categorise information or images, will become increasingly significant.

There’s always going to be some level or objectivity/subjectivity to any image. A webmaster can take steps to help a search engine by using a file name, alt text, a caption, and even other text on a page that might be associated with an image.

If that webmaster wants people to look at the image, and be able to understand what the image is about without looking at that text, it doesn’t hurt to choose the best picture possible, and limit some of that subjectivity. So, if I was writing a page about the FBI, and I wanted to choose a picture that made it clear that people in the picture were FBI agents, I would try really hard to make sure I got a shot of at least one of those people wearing one of those blue jackets that FBI agents sometimes wear that have “FBI” on the back in big yellow letters – and that the “FBI” was clearly visible to viewers of the page.

The ideas behind games like the ESP game and the treasure search are examples of crowdsourcing in action. Google didn’t acquire the ESP game, but rather licensed some of the technology behind it for the Image Labeler game.

I’m not really sure much profiling is actually going on in what is described in this patent filing. The idea instead is to create games that might help solve problems that computers might not be so good at solving on their own.