-- とある白い猫 (To Aru Shiroi Neko)

On Mon, Sep 26, 2011 at 18:43, Paul Houle <paul@ontology2.com> wrote:

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.

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