ZMP INC.
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Open Source Photogrammetry: Ditching 123D Catch – We Did Stuff
This is part one in a series on open source photogrammetry. In part two, I’ll flesh out more VFX-centric application of this workflow. Before I start, big thanks to: Dan Short: for showing me his awesome 123d models that sparked this whole idea Hannah Davis: debugging + emotional support + snacks So a few weeks ago, Dan Short showed me 123D Catch. It was awesome. You feed in some pictures from you
Make: Japan | Autodeskã¨Circuits.ioãŒç„¡æ–™ã®é›»å回路デザインツールを共åŒé–‹ç™º
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openMVG: "open Multiple View Geometry"
"open Multiple View Geometry" is a library for computer-vision scientists and especially targeted to the Multiple View Geometry community. It is designed to provide an easy access to the classical problem solvers in Multiple View Geometry and solve them accurately. The openMVG credo is: "Keep it simple, keep it maintainable". OpenMVG targets readable code that is easy to use and modify by the comm
Bundler - Structure from Motion for Unordered Image Collections
Bundler: Structure from Motion (SfM) for Unordered Image Collections Software written by Noah Snavely Download Bundler from the bundler_sfm repository on GitHub | What is Bundler? | Downloading Bundler | Documentation | References | Links | What is Bundler? Bundler is a structure-from-motion (SfM) system for unordered image collections (for instance, images from the Internet) written in C and C++.
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Versa Connector (TNDCI DEV) 0.0.1 - Sign On
By signing on to this system you are agreeing to follow the stated security policy. This is a Government computer system and is intended for official and other authorized use only. Unauthorized access or use of the system may subject violators to administrative action, civil, and/or criminal prosecution under the Criminal Code (Title 18 USC 1030). All info on this computer system may be monitored,
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Using OpenCV to generate 3d points (assuming frontal parallel configuration)
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Surfer - 3D Surface Maps
https://cs.stanford.edu/~asaxena/learningdepth/saxena_ijcv07_learningdepth.pdf
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