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CPU implementation of "Pixelwise View Selection for Unstructured Multi-View Stereo (Schönberger et al.)"

License: Mozilla Public License 2.0

CMake 1.94% C++ 98.06%
point-cloud dense-reconstruction fusion multiview-stereo mvs

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pwmvs's Issues

CMake Error(OpenMVG is not found)

CMake Error at G:/PWMVS/openMVG-master/src/bin/OpenMVGConfig.cmake:47 (message):
  Failed to find OPENMVG - OpenMVG install root:
  G:/PWMVS/openMVG-master/src/bin.  Cannot find openMVG include files.
Call Stack (most recent call first):
  G:/PWMVS/openMVG-master/src/bin/OpenMVGConfig.cmake:83 (OPENMVG_REPORT_NOT_FOUND)
  CMakeLists.txt:4 (find_package)


CMake Error at G:/PWMVS/openMVG-master/src/bin/OpenMVGConfig.cmake:48 (else):
  A duplicate ELSE command was found inside an IF block.
Call Stack (most recent call first):
  G:/PWMVS/openMVG-master/src/bin/OpenMVGConfig.cmake:83 (OPENMVG_REPORT_NOT_FOUND)
  CMakeLists.txt:4 (find_package)


Configuring incomplete, errors occurred!
G:PWMVS/
|-- OpenMVG-master/
    |-- src
        |-- bin(build folder)
            |-- OpenMVGConfig.cmake
|-- pwmvs-master/

Windows 10
VisualStudio 2017
CMAKE(GUI)

use all neighboring images when fusing

When fusing we project point only to images that were used in depthmap generation. Extend this selection to all images that share tie points (tracks).

Readme ?

Hello,

I would like to get dense reconstruction inside Colmap, as I am working on macOs and don't have an NVIDIA graphic card with CUDA.

Would you mind sharing few lines in a readme or in this topic on how to install your program ?
Does it require OpenMVG and/or OpenMVS ?
How do I tell Colmap to use PWMS for the dense reconstruction step ?

Many Thanks

wrong array index used

evaluations[h] += options.geometric_consistency_weight * geometric_consistency_calculator(*src, convertToFloat(x), hypotheses[i].depth);

instead of hypotheses[i] there should be hypotheses[h]

Use proper 3D median filtering

At the moment we find median value for each coordinate (and color channel) separately when fusing depth maps. Try to find best median value considering all dimensions.

One possible option is to use Weiszfeld's algorithm. Algorithm should need very little iterations to find good solution.

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