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Jay Dugger's Library tagged 3d →  View Popular

14 Feb 09

Shapeways | passionate about creating

Welcome to Shapeways.

* We want to be a fun, inspiring place where you make your own 3D designs come to life using 3D printing.
* You can then keep those 3D printed models for yourself, give them away as a gift or even sell them in the Shapeways

www.shapeways.com - Preview

design for:rogerwaggener for:makemagazine fabrication 3d for:bekathwia

Wikitecture Progress, Second Life Machinima, 3D Wiki

Studio Wikitecture machinima in Second Life, showing progress on the Open Architecture Challenge in Second Life. 3D Wiki interface, architectural collaboration, Building Information Model (BIM) technology.

www.youtube.com/watch - Preview

secondlife wiki collaboration architecture bim opensource 3d 3dwiki wikitecture video youtube year:2008 month:02 day:10 machinima for:anissimov for:dv82xl for:rogerwaggener for:librarianbyday

18 Apr 08

LandPrint.com: 3D Print Your World!

Now you can create custom 3D models of your favorite places. Through the magic of 3D printing, personalized replicas of vacation spots, journeys and natural wonders are just a few clicks away …

www.landprint.com/...index.html - Preview

3d mapping printing hardware for:bekathwia for:anissimov for:makemagazine for:rogerwaggener service fabrication worldwind

Google KML

  • KML, or Keyhole Markup Language, is an XML grammar and file format for modeling and storing geographic features such as points, lines, images, and polygons for display in Google Earth™, Google Maps™, and Google Maps for mobile. - jaydugger on 2007-02-05

BlenderNation

  • Fresh Blender News, Every Day - jaydugger on 2007-02-05

blender.org :: Home

  • Blender is the open source software for 3D modeling, animation, rendering, post-production, interactive creation and playback. Available for all major operating systems under the GNU General Public License. - jaydugger on 2007-02-05

Multi-View Stereo for Community Photo Collections

  • We present a multi-view stereo algorithm that addresses the extreme changes in lighting, scale, clutter, and other effects in large online community photo collections. Our idea is to intelligently choose images to match, both at a per-view and per-pixel level. We show that such adaptive view selection enables robust performance even with dramatic appearance variability. The stereo matching technique takes as input sparse 3D points reconstructed from structure-from-motion methods and iteratively grows surfaces from these points. Optimizing for surface normals within a photoconsistency measure significantly improves the matching results. While the focus of our approach is to estimate high-quality depth maps, we also show examples of merging the resulting depth maps into compelling scene reconstructions. We demonstrate our algorithm on standard multi-view stereo datasets and on casually acquired photo collections of famous scenes gathered from the Internet.
     - jaydugger on 2007-11-04
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