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The project is based on the COLMAP framework. Please refer to https://colmap.github.io/ for more information like installation and tutorial. The usage of this application is similair to that of COLMAP. We demonstrate one example of command-lines applying PLC on Linux below. The main differerences from COLMAP command-lines lay on the 'colmap patch_match_stereo' block where we add options for applying pyramid architecture and local consistency.


LD_LIBRARY_PATH=/opt/Qt5.12.0/5.12.0/gcc_64/lib/ iname=$1/ gpu=$2 filter=$3 depth_error=$4 reproj_error=$5 PROJECT_PATH=${iname}result DATABASE=${iname}sample_reconstruction.db

mkdir ${PROJECT_PATH} mkdir ${PROJECT_PATH}/images cp -n ${iname}*.jpg ${PROJECT_PATH}/images

colmap feature_extractor
--database_path ${DATABASE}
--image_path ${PROJECT_PATH}/images
--ImageReader.camera_model RADIAL
--ImageReader.single_camera 1
--SiftExtraction.use_gpu 1
--SiftExtraction.gpu_index ${gpu}

colmap exhaustive_matcher
--database_path ${DATABASE}
--SiftMatching.use_gpu 1
--SiftMatching.max_num_matches 10000
--SiftMatching.gpu_index ${gpu}

mkdir ${PROJECT_PATH}/sparse colmap mapper
--database_path ${DATABASE}
--image_path ${PROJECT_PATH}/images
--output_path ${PROJECT_PATH}/sparse

mkdir ${PROJECT_PATH}/dense

colmap image_undistorter
--image_path ${PROJECT_PATH}/images
--input_path ${PROJECT_PATH}/sparse/0/
--output_path ${PROJECT_PATH}/dense
--output_type COLMAP

colmap patch_match_stereo
--workspace_path ${PROJECT_PATH}/dense
--workspace_format COLMAP
--PatchMatchStereo.filter true
--PatchMatchStereo.geom_consistency true
--PatchMatchStereo.gpu_index ${gpu}
--PatchMatchStereo.pyramid_stereo_match 3
--PatchMatchStereo.pyramid_stereo_match_l 0
--PatchMatchStereo.smoothness 0.99
--PatchMatchStereo.num_iterations 5

colmap stereo_fusion
--workspace_path ${PROJECT_PATH}/dense
--workspace_format COLMAP
--input_type geometric
--StereoFusion.min_num_pixels 5
--StereoFusion.max_num_pixels 1000
--StereoFusion.max_depth_error $depth_error
--StereoFusion.max_reproj_error $reproj_error
--output_path ${PROJECT_PATH}/dense/fused_1.ply


If you find this work helpful for you, please cite our paper and "Pixelwise View Selection for Unstructured Multi-View Stereo".

@article {10.1111:cgf.13841, journal = {Computer Graphics Forum}, title = {{Pyramid Multi-View Stereo with Local Consistency}}, author = {Liao, Jie and Fu, Yanping and Yan, Qingan and Xiao, Chunxia}, year = {2019}, publisher = {The Eurographics Association and John Wiley & Sons Ltd.}, ISSN = {1467-8659}, DOI = {10.1111/cgf.13841} }

@inproceedings{schoenberger2016mvs, author={Sch"{o}nberger, Johannes Lutz and Zheng, Enliang and Pollefeys, Marc and Frahm, Jan-Michael}, title={Pixelwise View Selection for Unstructured Multi-View Stereo}, booktitle={European Conference on Computer Vision (ECCV)}, year={2016}, }

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Implementation of paper "Pyramid Multi-View Stereo with Local Consistency" based on COLMAP framework

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