Rich Gibson wrote:
I have the precise same problem of having photographs and trying to extract meaning from the clusters. I've been working on code to scratch this itch, and I'd be happy to send it to anyone, or to work with someone else to generalize the solution. The code is in Perl.
I think one of the problems here is that we're quite often dealing with 'geography' in a wider sense than can be easily expressed in terms of clusters within an homogeneous cartesian space. As an example, I may have a bunch of photos taken in Chamonix, France and another bunch taken in Aosta, Italy. These could be crudely clustered into two groups, one for each town. However, none of these photos are of either Chamonix or Aosta, but of the mountain Mont Blanc, which is visible from both towns. Factoring in other location-based information such as direction, may help here, as would viewsheds. I wonder too if histogram-based analysis of image content may be useful here (eg a largely blue and white image facing in a given direction at a given point it likely to be a mountain)
Another issue is that of clustering around linear features. Similar to above, I may have photos taken of bridges at towns crossing a particular river. Whilst each photo would (correctly) be clustered with the town it was taken in, each photo too would be grouped with the others taken along that same river.
Anyway...I am very interested in these thoughts. I'd love to collaborate with you, or anyone else, on these areas. I'm currently working in Perl and Ruby on Rails using MySQL and Postgis.
+1. This is an area that interests me greatly. FWIW I'm Perl/C++/PHP. I've been genericising, adapting and coding some clustering functionality as a bunch of PHP classes recently. Hope to turn it into an article someday.
Cheers, Andrew _______________________________________________ Geowanking mailing list [email protected] http://lists.burri.to/mailman/listinfo/geowanking
