Automatic Image Tagging

bignickel writes "Researchers at Penn State have applied for a patent on software that automatically recognizes objects in photos and tags them accordingly. The 'Automatic Linguistic Indexing of Pictures Real-Time' software (catchy name) trained a database using tens of thousands of images, and new images have 15 tags suggested based on comparisons with objects or concepts in the database. Not sure how you identify a 'concept,' and they're only talking about having one correct tag in the top 15, but still cool."

The other 50% is the problem

[Heir Of The Mess]

I've seen lots of systems like this. The problem is in the 50% of the images that don't work, so basically you have to manually tag 50% of your images.

I saw an interesting one about 10 years ago. It took an X-Ray image, did an edge detection, converted all the edges to a slope vs distance 2D plot, and conerted edge curves to a radius and distance plot, then used a kind of statistical correlation algorithm to pick which part of the body the image was from. I could imagine that you could apply something similar to the luminance of an image to pick out objects, and then maybe do some color transforms and stuff to improve results. The article says they do it in 1.4 seconds per image though, which is impressive.

Re:That Sucks

[Nybarius]

Contrary to what you might believe, there is nothing unethical about making money. The government even gives out grants for entrepreneurs, and lets them keep all the profits; it's good for the economy, overall. The profit motive is a much more powerful incentive to positive social change than the goodness that lies in the hearts of men,

-Nyb

A video an the subject

[damgx]

Luis Van Ahn did something almost the same, his idea though is to use humans aswell.

View the video on Human Computation [google.com]

XRay much easier though

[SuperKendall]

The human body is pretty much the same between people, and XRays are generally shot from similar directions person to person - so the kind of check you are describing seems like it would yield high matches for pretty much any part of the body.

In the real world we have an object you might take a picture of from any angle, using a myriad of focal lengths, with variable levels of distorition depending on the lens and camera used. Really nasty for generic object recognition. I think the best we can hope for in terms of accuracy is perhaps some kind of facial recognition autmatically recognizing and tagging people in images.