- 22 Jul, 2014 4 commits
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Mathias Goldau authored
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Mathias Goldau authored
[FIX #373] Due to the update change of #373 there was a minor update bug: When new data was connected, no update took place.
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Mathias Goldau authored
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Mathias Goldau authored
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- 19 Jul, 2014 1 commit
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Andreas Schwarzkopf authored
* This approach describes the surface detection of Zahra Lari and Ayman Habib (2014). * Paper: "An adaptive approach for the segmentation and extraction of planar * andlinear/cylindrical features from laser scanning data", ISPRS Journal of * Photogrammetry and Remote Sensing, 2014 * * Eventually the process covers also the linear and cylindrical feature segmentation * but in our requirements only the planar segmentation is required. Steps: * - Original laser point cloud as input data * - PCA-based classification of planar features * - Selection of appropriate representation models for the detected planar features * - Local point density estimation along the detected planar features * - Precise estimation of the planar features segmentation attributes * - Parameter-domain segmentation and extraction of planar features * - Boundary tracking for resolving the parameter-domain segmentation ambiguities of * planar features * - Extracted planar features in spatial domain * * Estimations (Based on the paper because I haven't completely impelemented yet): * - Fair segmentation results * - Relatively slow * * Implementation progress: * - Done to the step "Precise estimation of the planar features segmentation * attributes". * * * Other updates: * - Renamed module "Pooints - Crop" to "Points - Transform". It optained the feature * to translate and to rotate the point set. * - Wew code refactoring.
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- 15 Jul, 2014 2 commits
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Mathias Goldau authored
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Mathias Goldau authored
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- 20 Jun, 2014 1 commit
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Andreas Schwarzkopf authored
* Currently the module Surface detection by PCL only gives the ability to detect * surfaces using point clouds (WDataSetPoints) what is a method of a fair quality. * * Some few changes across other modules: * - Improvement on the octree neighbor search algorithm. Now you can look for * neighbors using the neighborship of 6, 18 or 26 * - Very first steps on the surface detection algorithm "An adaptive approach for the * segmentation and extraction of planar and linear/cylindrical features from laser * scanning data" of Lari/Habib (2014). * - Added an unidimensional kd tree structures with some processing methods such as * looking for nearest nghbors.
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- 21 May, 2014 1 commit
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Andreas Schwarzkopf authored
* I changed in the WPrincipalComponentAnalysis analyzeData(const vector<WPosition>) to * analyzeData(const vector<WPosition>*) in order to avoid unnecessary copies. Therefore * some classes had to be changed to remain compilable.
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- 19 May, 2014 2 commits
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Alexander Wiebel authored
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Alexander Wiebel authored
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- 16 May, 2014 3 commits
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Alexander Wiebel authored
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Alexander Wiebel authored
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Andreas Schwarzkopf authored
* Added a new outline method to the wall detection. Voxels or properties of its * input point data can be displayed using rhombs. They display the wall node group, * Eigen Vectors, Eigen Values and the mean coordinate. * * Applied fixes: * The wall detection failed by bleeding through several surfaces. The problem was * that no angle condition was applied during merging wall groups. * Also small cleanups were applied on the code.
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- 06 May, 2014 1 commit
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aschwarzkopf authored
* The algorithm is intended to grouup voxels that have surfaces with the same * normal vector. This feature helps to remove small groups. Obviously trees * by nature have points that lead the Principal Component Analysis to * surfaces that have very different Eigen Vectors of the smallest Eigen Value * that is the normal vector in the case of surfaces. * * Other feature: Removing voxels by a point count per voxel.
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- 05 May, 2014 2 commits
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aschwarzkopf authored
* The new module firstly puts point data into a voxel grid. For each of these areas * the Principal Component Analysis is run. For each voxel the Eigen Vector of the * smallest Eigen Value is taken. In the case of surface kins data it's the normal * vector. In the last steps voxels with the similar vector are grouped. * Currently the region growing often bleeds over through many surfaces.
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aschwarzkopf authored
* This algorithm puts input point coulds to a voxel grid and applies the Principal * Component Analysis to each of these areas. It's calculated how isotropic voxels are. * Either planar voxels have the blue color and isotropic ones are red. There's a * feature to cut avay voxels from the output triangle mesh for the view. You can either * set the minimal point count per voxel or the quotient of the smallest Eigen value over * the biggest one as the maximal isotropic level criteria.
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- 19 Apr, 2014 1 commit
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Mathias Goldau authored
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- 16 Apr, 2014 1 commit
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Mathias Goldau authored
[CHANGE] Many improvements over time. Outlining, Stratified and regular samplers, shader improvements and shader debugging code,...
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- 18 Mar, 2014 2 commits
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Mathias Goldau authored
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Mathias Goldau authored
[ADD] Global Boy coloring, as well as custom colors in StartEnd Coloring. This enables illumination for singe color as well.
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- 03 Mar, 2014 1 commit
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Mathias Goldau authored
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- 02 Mar, 2014 2 commits
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Mathias Goldau authored
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Mathias Goldau authored
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- 19 Feb, 2014 1 commit
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aschwarzkopf authored
Following bugfixes new features: - Points group selector plugin: Can output selected buildings as WDataSetPointsGrouped in order to be able to view data in other plug-ins - Elevation image export plugin: Features to switch elevation display in triangle mesh height and color. - Fixes in documentation and few code cleanup.
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- 18 Feb, 2014 1 commit
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aschwarzkopf authored
The buildings detection plugin generally was a mix of many things. These things of it were split up into these plutins: - Elevation image export - Points group selector which transforms building groups into a voxel structure and exports it to a triangle mesh. Added features: - Elevation image can be output in a triangle mesh - Elevation image (file and triangle mesh output) and building outline got colored building outline Code style: - Fixed prooblems with documentation (make doc) - Purged last code style (make stylecheck)
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- 20 Jan, 2014 4 commits
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Mathias Goldau authored
[FIX] RGBA used an invalid alpha for lineAO, so as we do not need it here, we just use RGB for coloring the start-end.
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Mathias Goldau authored
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Mathias Goldau authored
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Mathias Goldau authored
[ADD] New start-end color coding for fibers. Currently only red-white is possible and hard coded as I am not aware of any colorscales as Properties. It would be possible to define one, but this is deferred to the time when really needed.
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- 16 Jan, 2014 1 commit
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Mathias Goldau authored
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- 07 Jan, 2014 2 commits
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Alexander Wiebel authored
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Alexander Wiebel authored
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- 05 Jan, 2014 1 commit
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aschwarzkopf authored
Some simplistic algorithms are done in order to group buildings. Evaluation: + Important data structures as Octree and Quadtree are implemented with important functions + Grouping neighbor voxels runs even if still not 26-neighborship (few steps required) + Algorithm can easily be transferred to the quadtree set. + First new plugin for cutting of outlier points using the algorithm that calculates figuring out cube connectivity. Other points are cut off that don't belong to the largest voxel group - Possibly vaporized effort - The algorithm that takes relative elevation minimums has problems detecting low buildings. - Probably the algorithm won't be taken + The great deal of the code amount used for it can be very useful for the final code. + It's easy to differ trees from buildings - Not thought to the end to differ trees that are very close to buildings
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- 02 Jan, 2014 1 commit
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aschwarzkopf authored
* This is a first important intermediate step for making sure having a * consistent data structure that has an elevation image which has an * important role in building detection.
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- 13 Dec, 2013 2 commits
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Mathias Goldau authored
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Mathias Goldau authored
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- 11 Dec, 2013 3 commits
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aschwarzkopf authored
Removing a file that I've created by mistake
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aschwarzkopf authored
Done few very first steps for building detection: - Areas that contain data set points, are outlined by octree nodes - Ability to draw that outline as boxes in order to be able to draw very huge las files at all.
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aschwarzkopf authored
Just started very first building detection implementation steps: - Transforming point data to octree nodes - Ability to display LAS data as boxes, but without color intensity display. Now you don't need vast amount of RAM (32GB for a 500MB las file) and GPU memory to be able to display larger las files at all.
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