I think the idea has merit. Use traditional close-range photogrammetry with consummer-grade digital cameras to create geo-referenced 3d models. OpenCV has some 3d model construction from stereo imagery functions (Nasa's Vision workbench may be an alternative).
I'm not clear on the usefulness of voxels in this context. Best Regards, Brent Fraser > I wanted to just share the observation that it might be time for us all as > a > community to look at building a kind of open photosynth - what could be > called an 'open voxel space' map of the planet. > > Microsoft's photosynth project stitches together a series of arbitrary > user > photographs of a scene, taken from different angles and perspective and > melds into a single seamless 3d image of that setting. The way this works > is that each image has notable feature points on it, and between any two > images there may be zero or more shared feature points. If you have > enough > similar feature points then you can effectively say that these two images > overlap each other in some way. Given two photographs of a building, say > from two people standing at two different places, you can start to > re-constitute a 3d voxel model of that building from just those two > photographs. > > The goal would be to start collecting all photographs and building an open > 3d model of the photographed planetary surface of earth. Basically one > would be building a kind of open voxel space - a 3d model of our cities > and > spaces - and this could help with other projects. > > The algorithms are not hard to use, there are open source implementations > (google SIFT) - and even if they algorithms suck right now they will > improve > over time. It's mostly just a scaling problem; how and where to aggregate > or index or store the images. In fact I strongly recommend at least > playing > with one of the open source SIFT implementations - it is a lot of fun and > gives you a taste for the possibilities. > > Generally I feel that the best data is more data. An Open Voxel Space > could > help with lots of other problems. We define and attach labels to streets > as > a way of doing a kind of manual position sensing. We of course care to > know > about streets and paths because we cannot walk through walls. > > Good voxel data could help fix up bad GPS data among other things... and > it > would help increase the usability of GPS data therefore and reduce the > necessity for thinking about streets and labels. With enough good data a > router would simply pick from the most common recent existing full gps > track > between the two points... > > Also (and this is less firm, more speculative, but still seems marginally > relevant): maybe a voxel map of space; that wasn't just focusing on > labelled > streets or paths, but on space in general, might also help with the puzzle > of better delivering real time and volatile data to people - "just in time > knowlege" - the "help I lost a kitten" kinds of stuff. It's unclear to me > why there isn't really a kind of real-time bartering service yet - perhaps > twitter is closest - but one that focuses more on discrete signalling for > very specific services; rather than just "saying"... Maybe a better map of > space could help - maybe the issue is that "distance" between things is > blocked by buildings in a way that street-maps don't quite convey and when > that is not clearly factored in it acts as a barrier to surmounting > distance? > > _______________________________________________ > Geowanking mailing list > [email protected] > http://lists.burri.to/mailman/listinfo/geowanking > _______________________________________________ Geowanking mailing list [email protected] http://lists.burri.to/mailman/listinfo/geowanking
