On 9/20/2011 9:36 AM, とある白い猫 wrote:
The conference has no such tool yet, at least nothing
we can
use tomorrow but they are able to pretty accurately on what the images
are. I am going to try to propose if they would be interested in
providing commons with such a service, The website relevant is
http://www.imageclef.org/2011/Wikipedia for commons but
http://www.imageclef.org/2011/Plants is also interesting (even though
it had nothing to do with commons so far. It could ver well be used
for commons and wikispecies alike.
-- とある白い猫 (To Aru Shiroi Neko)
I've made some attempt to map images on Wikimedia commons to
distinct concepts from DBpedia, see
http://ookaboo.com/
This could be useful for forming a training set, but I haven't
yet got around to releasing a public dump of the data. I have about 1
million things classified and could certainly extend the strategies used
to get more.
Unless there's been a really unprecedented breakthrough, I'd
think that the application of machine vision to Wikimedia faces the
problem of getting enough training data. If you had thousands or tens
of thousands of photos that were labeled 'cat' or 'not cat', or
'member
of plant species X' or 'not member of plant species X', you can train a
classifier to make the distinction. However, if you've got two or
three bad photos of a particular plant (which is what you have most of
the times in Commons) you don't have enough training data to generalize.
If you've got a specific mission, say genitals recognition, I
think you can make progress, but to attack the general problem you need
to go big with your training sets.