On 6/18/14, Kristian Kankainen <krist...@eki.ee> wrote: > Hello! > > I think, if one is clever enough, some categorization could be automated > allready. > > Searching for pictures based on meta-data is called "Concept Based Image > Retrieval", searching based on the machine vision recognized content of > the image is called "Content Based Image Retrieval". > > What I understood of Lars' request, is an automated way of finding the > "superfluous" concepts or meta-data for pictures based on their content. > Of course recognizing an images content is very hard (and subjective), > but I think it would be possible for many of these "superfluous" > categories, such as "winter landscape", "summer beach" and perhaps also > "red flowers" and "bicycle". > > There exist today many open source "Content Based Image Retrieval" > systems, that I understand basically works in the way that you give them > a picture, and they find you the "matching" pictures accompanied with a > score. Now suppose we show a picture with known content (pictures from > Commons with good meta-data), then we could to a degree of trust find > pictures with overlapping categories. > I am not sure whether this kind of automated reverse meta-data labelling > should be done for only one category per time, or if some kind of > "category bundles" work better. Probably adjectives and items should be > compounded (eg "red flowers"). > > Relevant articles and links from Wikipedia: > # https://en.wikipedia.org/wiki/Image_retrieval > # https://en.wikipedia.org/wiki/Content-based_image_retrieval > # > https://en.wikipedia.org/wiki/List_of_CBIR_engines#CBIR_research_projects.2Fdemos.2Fopen_source_projects > > Best wishes > Kristian Kankainen > > 18.06.2014 09:14, Pine W kirjutas: >> Machine vision is definitely getting better with time. We have >> computer-driven airplanes, computer-driven cars, and computer-driven >> spacecraft. The computers need us less and less as hardware and software >> improve. I think it may be less than a decade before machine vision is >> good >> enough to categorize most objects in photographs. >> >> Pine >> _______________________________________________ >> Wikitech-l mailing list >> Wikitech-l@lists.wikimedia.org >> https://lists.wikimedia.org/mailman/listinfo/wikitech-l >> > > > _______________________________________________ > Wikitech-l mailing list > Wikitech-l@lists.wikimedia.org > https://lists.wikimedia.org/mailman/listinfo/wikitech-l
Interesting. Some demo links that I found: * http://demo-itec.uni-klu.ac.at/liredemo/ * http://image.mdx.ac.uk/time/demo.php * http://mi-file.isti.cnr.it:8765/CophirSearch/ * http://orpheus.ee.duth.gr/anaktisi/ (not free) * http://youtu.be/2eaGwk4Xhks I suppose one integration pathway would be, you do a normal search, and then from there you can say, find images similar to this search result. Of course if I do https://commons.wikimedia.org/w/index.php?title=Special:Search&search=bicycle%20red%20flower&fulltext=Search&profile=images , the first result is relavent. But if I plug https://upload.wikimedia.org/wikipedia/commons/thumb/f/f7/2009_windowboxes_Bruges_4064497113.jpg/450px-2009_windowboxes_Bruges_4064497113.jpg into http://demo-itec.uni-klu.ac.at/liredemo/ , the results aren't really that relavent. --bawolff _______________________________________________ Wikitech-l mailing list Wikitech-l@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/wikitech-l
