In figures 5-7, I'm somewhat troubled by the fact that they've selected a handful of the topics out of the set of algorithm-discovered topics. It makes me wonder about the topics they didn't select.

I also wonder whether the algorithm could be adapted to partly labeled data (where (some of) the contents of a picture are labeled, but no knowledge of where they occur in the image is provided). Since it doesn't seem like this method is likely to scale well to cases where the data set isn't already set up to have a small selection of objects, it seems like these labels would already be available. (There isn't as much of a correlate in the text-mining community for this kind of approach, but...)