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- Iterative_closest_point abstract "Iterative Closest Point (ICP) is an algorithm employed to minimize the difference between two clouds of points. ICP is often used to reconstruct 2D or 3D surfaces from different scans, to localize robots and achieve optimal path planning (especially when wheel odometry is unreliable due to slippery terrain), to co-register bone models, etc.In the algorithm, one point cloud, the reference, or target, is kept fixed, while the other one, the source, is transformed to best match the reference. The algorithm iteratively revises the transformation (combination of translation and rotation) needed to minimize the distance from the source to the reference point cloud.Inputs: reference and source point clouds, initial estimation of the transformation to align the source to the reference (optional), criteria for stopping the iterations.Output: refined transformation.Essentially, the algorithm steps are: For each point in the source point cloud, find the closest point in the reference point cloud. Estimate the combination of rotation and translation using a mean squared error cost function that will best align each source point to its match found in the previous step. Transform the source points using the obtained transformation. Iterate (re-associate the points, and so on).Zhang proposes a modified K-D tree algorithm for efficient closest point computation. In this work a statistical method based on the distance distribution is used to deal with outliers, occlusion, appearance, and disappearance, which enables subset-subset matching.There exist many ICP variants, from which point-to-point and point-to-plane are the most popular. The latter usually performs better in structured environments.".
- Iterative_closest_point wikiPageExternalLink summary?doi=10.1.1.42.9338.
- Iterative_closest_point wikiPageExternalLink citation.cfm?id=2343006.
- Iterative_closest_point wikiPageExternalLink fasticp.
- Iterative_closest_point wikiPageExternalLink doku.php?id=laserregistration:laserregistration.
- Iterative_closest_point wikiPageExternalLink icpstability.pdf.
- Iterative_closest_point wikiPageExternalLink libicp.
- Iterative_closest_point wikiPageExternalLink 24301.
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- Iterative_closest_point wikiPageExternalLink b.
- Iterative_closest_point wikiPageExternalLink sparseicp.
- Iterative_closest_point wikiPageExternalLink libpointmatcher.
- Iterative_closest_point wikiPageID "1830232".
- Iterative_closest_point wikiPageLength "6392".
- Iterative_closest_point wikiPageOutDegree "13".
- Iterative_closest_point wikiPageRevisionID "680398462".
- Iterative_closest_point wikiPageWikiLink Algorithm.
- Iterative_closest_point wikiPageWikiLink Bone.
- Iterative_closest_point wikiPageWikiLink Category:Geometry_in_computer_vision.
- Iterative_closest_point wikiPageWikiLink Category:Robot_navigation.
- Iterative_closest_point wikiPageWikiLink CloudCompare.
- Iterative_closest_point wikiPageWikiLink GNU_General_Public_License.
- Iterative_closest_point wikiPageWikiLink Insight_Segmentation_and_Registration_Toolkit.
- Iterative_closest_point wikiPageWikiLink Iterative_method.
- Iterative_closest_point wikiPageWikiLink Mean_squared_error.
- Iterative_closest_point wikiPageWikiLink MeshLab.
- Iterative_closest_point wikiPageWikiLink PCL_(Point_Cloud_Library).
- Iterative_closest_point wikiPageWikiLink Point_Cloud_Library.
- Iterative_closest_point wikiPageWikiLink Point_set_registration.
- Iterative_closest_point wikiPageWikiLink VTK.
- Iterative_closest_point wikiPageWikiLinkText "ICP".
- Iterative_closest_point wikiPageWikiLinkText "Iterative closest point".
- Iterative_closest_point wikiPageWikiLinkText "iterative closest point".
- Iterative_closest_point hasPhotoCollection Iterative_closest_point.
- Iterative_closest_point subject Category:Geometry_in_computer_vision.
- Iterative_closest_point subject Category:Robot_navigation.
- Iterative_closest_point hypernym Algorithm.
- Iterative_closest_point type Software.
- Iterative_closest_point comment "Iterative Closest Point (ICP) is an algorithm employed to minimize the difference between two clouds of points. ICP is often used to reconstruct 2D or 3D surfaces from different scans, to localize robots and achieve optimal path planning (especially when wheel odometry is unreliable due to slippery terrain), to co-register bone models, etc.In the algorithm, one point cloud, the reference, or target, is kept fixed, while the other one, the source, is transformed to best match the reference.".
- Iterative_closest_point label "Iterative closest point".
- Iterative_closest_point sameAs Iterative_Closest_Point_Algorithm.
- Iterative_closest_point sameAs Iteracia_plej_proksima_punkto.
- Iterative_closest_point sameAs Iterative_Closest_Point.
- Iterative_closest_point sameAs Iteracyjny_najbliższy_punkt.
- Iterative_closest_point sameAs m.05_c5x.
- Iterative_closest_point sameAs Итеративный_алгоритм_ближайших_точек.
- Iterative_closest_point sameAs Q1675268.
- Iterative_closest_point sameAs Q1675268.
- Iterative_closest_point wasDerivedFrom Iterative_closest_point?oldid=680398462.
- Iterative_closest_point isPrimaryTopicOf Iterative_closest_point.