Hoi,
My understanding of English is adequate. I find it however really hard to
find the pictures I seek. I have given up using Commons for illustrations
on my blog for instance.
Thanks,
GerardM
On 18 June 2014 12:25, Kristian Kankainen <krist...@eki.ee> wrote:
> Could not the categories' language links be useful here? Otherwise
> BabelNet[1] has set up different ways to connect concepts in different
> languages into a semantic network. They call it a multilingual encyclopedic
> dictionary and compile it by combining data from the Wikipedia(s) and
> WordNet. It's quite clever but still easy.
> This is still english-centric -- as in having english in the centre of a
> hub-and-spoke modelled dictionary -- but it does make it _translatable_,
> which I think is enough for this feature.
>
> Kristian Kankainen
>
> [1] http://babelnet.org/
>
> 18.06.2014 11:52, Gerard Meijssen kirjutas:
>
> Hoi,
>> As long as our categories are English, they are useless for all of those
>> who do not speak English. Even so, as long as the current technology is
>> used for those categories it is a trial to find images at all. Many people
>> have given up.
>> Thanks,
>> GerardM
>>
>>
>> On 18 June 2014 09:12, 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
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