red3king

That's a good point, but we are a long way away from an automated general object recognition system. This discounts occasional outliers such as obvious objects which take up the whole page, or ones that are clearly visible against a gradient-less background (both of which can be pruned).

Currently, we are validating inputs from a human written database, which is continuously being expanded with new user inputs and new images. One image is used for validation, and the other is used for expanding the pool.

Hey Tyler,

You're right about certain images having easily distinguished objects-of-interest. In the future, running a routine to weed those easy ones out will stop any being solvable by bots. And also, as with any other captcha, paying other humans to validate themselves for you will always be an issue.

We validate users' inputs against a pool of manually-entered data. Because we collect a pair of annotations for each submission, one is used to verify the user, and the other is collected against an un-annotated image. As annotations are collected for new images, they are synthesized to expand the pool of annotated images.