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Just spitballing, could you do this by asking humans to differentiate two images that have been classified the same way? For example, for the pocket square set
by Qworg 13y ago
Just spitballing, could you do this by asking humans to differentiate two images that have been classified the same way?
For example, for the pocket square set, once there's a reasonable single cluster, could you randomly choose images (or ask "are these the same?") and ask what is different about the two images.
You may not get a formal taxonomy, but after enough of this, you could have something experts could work on. The problem, of course, is that without expert level insight, you'll get a lot of "that one is prettier".
- genevievemp 13y agoI've done a similar thing trying to create classifiers for scenes and buildings. It's hard to have a word for 'bottom left corner of a window with bars on it', for example. And for scenes there's no taxonomy in advance. I think it works better than expected (as good as automatic patch discovery methods), but you end up having to train a lot more classifiers because you'll get a number of redundant classifiers. Something that might be cool is to have a step where the common people try to do the clustering, and an expert corrects them if they do something not useful. Then there'd be a back and forth between experts and crowd people. I haven't really thought that out though.