From 9a49a6bc2dc723d4e081f66141ddc5a2f4111b27 Mon Sep 17 00:00:00 2001 From: Simone Gasparini Date: Thu, 28 May 2020 21:37:12 +0200 Subject: [PATCH] [bib] fixes --- source/node-reference/nodes/DepthMap.rst | 2 +- source/refs.bib | 79 ++++++++++++++---------- 2 files changed, 49 insertions(+), 32 deletions(-) diff --git a/source/node-reference/nodes/DepthMap.rst b/source/node-reference/nodes/DepthMap.rst index 7a504e0..4400924 100644 --- a/source/node-reference/nodes/DepthMap.rst +++ b/source/node-reference/nodes/DepthMap.rst @@ -46,7 +46,7 @@ Output Output folder for generated depth maps **Detailed description** -For all cameras that have been resolved by SfM, we want to retrieve the depth value of each pixel. Many approaches exist, like Block Matching, Semi-Global Matching (SGM) :cite:`Hirschmüller2005`, :cite:`Hirschmüller2008` or ADCensus :cite:`Xing2011`. We will focus on the SGM method implemented in AliceVision. +For all cameras that have been resolved by SfM, we want to retrieve the depth value of each pixel. Many approaches exist, like Block Matching, Semi-Global Matching (SGM) :cite:`Hirschmüller2005`, :cite:`Hirschmüller2008` or ADCensus :cite:`Mei2011`. We will focus on the SGM method implemented in AliceVision. For each image, we select the N best/closest cameras around. We select fronto-parallel planes based on the intersection of the optical axis with the pixels of the selected neighboring cameras. This creates a volume W, H, Z with many depth candidates per pixel. We estimate the similarity for all of them. The similarity is computed by the Zero Mean Normalized Cross-Correlation (ZNCC) of a small patch in the main image reprojected into the other camera. This create a volume of similarities. For each neighboring image, we accumulate similarities into this volume. This volume is very noisy. We apply a filtering step along X and Y axes which accumulates local costs which drastically reduce the score of isolated high values. We finally select the local minima and replace the selected plane index with the depth value stored into a depth map. This depth map has banding artifacts as it is based on the original selection of depth values. So a refine step is applied to get depth values with sub-pixel accuracy. diff --git a/source/refs.bib b/source/refs.bib index 260b048..3f72a4e 100644 --- a/source/refs.bib +++ b/source/refs.bib @@ -1,51 +1,68 @@ @misc{AVCameraLocalization, -title={AlicevisionCameraLocalization}, -url={ https://alicevision.github.io/#photogrammetry/localization}, -journal={alicevision.github.io}, -publisher={Alicevision} + title = {AlicevisionCameraLocalization}, + url = { https://alicevision.github.io/#photogrammetry/localization}, + howpublished = {alicevision.github.io}, + publisher = {Alicevision} } @inproceedings{Kneip2011, -author = {Kneip, Laurent and Scaramuzza, Davide and Siegwart, Roland}, -year = {2011}, -month = {06}, -pages = {2969-2976}, -title = {A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation}, -booktitle = {CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, -journal = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, -doi = {10.1109/CVPR.2011.5995464} + author = {Kneip, Laurent and Scaramuzza, Davide and Siegwart, Roland}, + year = {2011}, + month = {06}, + pages = {2969-2976}, + title = {A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation}, + booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, + doi = {10.1109/CVPR.2011.5995464} } @misc{OpenCVcameraCalibration, -title={Camera calibration With OpenCV}, -url={http://docs.opencv.org/3.0-beta/doc/tutorials/calib3d/camera_calibration/camera_calibration.html; https://web.archive.org/web/20200528170603/https://docs.opencv.org/3.0-beta/doc/tutorials/calib3d/camera_calibration/camera_calibration.html}, -journal={Camera calibration With OpenCV - OpenCV 3.0.0-dev documentation}, publisher={OpenCV} + title = {Camera calibration With OpenCV}, + url = {http://docs.opencv.org/3.0-beta/doc/tutorials/calib3d/camera_calibration/camera_calibration.html; https://web.archive.org/web/20200528170603/https://docs.opencv.org/3.0-beta/doc/tutorials/calib3d/camera_calibration/camera_calibration.html}, + howpublished = {Camera calibration With OpenCV - OpenCV 3.0.0-dev documentation}, publisher = {OpenCV} } @inproceedings{Hirschmüller2005, -author = {H. Hirschmüller}, -year = {2005}, -title = {Accurate and efficient stereo processing by semi-global matching and mutual information}, -booktitle = {CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition}, + doi = {10.1109/cvpr.2005.56}, + url = {https://doi.org/10.1109/cvpr.2005.56}, + publisher = {{IEEE}}, + author = {H. Hirschmuller}, + title = {Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information}, + booktitle = {2005 {IEEE} Computer Society Conference on Computer Vision and Pattern Recognition ({CVPR}{\textquotesingle}05)} } -@inproceedings{Hirschmüller2008, -author = {H. Hirschmüller}, -year = {2008}, -title = {Stereo processing by semiglobal matching and mutual information} +@article{Hirschmüller2008, + doi = {10.1109/tpami.2007.1166}, + url = {https://doi.org/10.1109/tpami.2007.1166}, + year = {2008}, + month = feb, + publisher = {Institute of Electrical and Electronics Engineers ({IEEE})}, + volume = {30}, + number = {2}, + pages = {328--341}, + author = {H. Hirschmuller}, + title = {Stereo Processing by Semiglobal Matching and Mutual Information}, + journal = {{IEEE} Transactions on Pattern Analysis and Machine Intelligence} } @inproceedings{Strecha2006, -author = {C. Strecha, R. Fransens, L. Van Gool}, -year = {2006}, -title = {Combined depth and outlier estimation in multi-view stereo}, -booktitle = {CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition} + doi = {10.1109/cvpr.2006.78}, + url = {https://doi.org/10.1109/cvpr.2006.78}, + publisher = {{IEEE}}, + author = {C. Strecha and R. Fransens and L. Van Gool}, + title = {Combined Depth and Outlier Estimation in Multi-View Stereo}, + booktitle = {2006 {IEEE} Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 ({CVPR}{\textquotesingle}06)} } -@inproceedings{Scharstein2002, -author = {D. Scharstein, R. Szeliski}, -year = {2002}, -title = {A taxonomy and evaluation of dense two-frame stereo correspondence algorithms} +@article{Scharstein2002, + doi = {10.1023/a:1014573219977}, + url = {https://doi.org/10.1023/a:1014573219977}, + year = {2002}, + publisher = {Springer Science and Business Media {LLC}}, + volume = {47}, + number = {1/3}, + pages = {7--42}, + author = {Daniel Scharstein and Richard Szeliski}, + journal = {International Journal of Computer Vision} } @inproceedings{Mei2011,