2-D ICP for PCL












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The ICP module in PCL is used specifically for 3-dimensional point clouds, i.e. there can be 3D transformations. Is there a way to implement 2D ICP in PCL, i.e. the z is fixed and transformations must be 2D?










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    The ICP module in PCL is used specifically for 3-dimensional point clouds, i.e. there can be 3D transformations. Is there a way to implement 2D ICP in PCL, i.e. the z is fixed and transformations must be 2D?










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      The ICP module in PCL is used specifically for 3-dimensional point clouds, i.e. there can be 3D transformations. Is there a way to implement 2D ICP in PCL, i.e. the z is fixed and transformations must be 2D?










      share|improve this question













      The ICP module in PCL is used specifically for 3-dimensional point clouds, i.e. there can be 3D transformations. Is there a way to implement 2D ICP in PCL, i.e. the z is fixed and transformations must be 2D?







      point-cloud-library point-clouds






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      asked Nov 12 at 3:12









      stan25

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          Under registration module, you can find pcl::registration::TransformationEstimation2D<...>. This class expects the two input point clouds to be aligned vertically and also the correspondences estimated a priori as explained here.






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            Under registration module, you can find pcl::registration::TransformationEstimation2D<...>. This class expects the two input point clouds to be aligned vertically and also the correspondences estimated a priori as explained here.






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              Under registration module, you can find pcl::registration::TransformationEstimation2D<...>. This class expects the two input point clouds to be aligned vertically and also the correspondences estimated a priori as explained here.






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                Under registration module, you can find pcl::registration::TransformationEstimation2D<...>. This class expects the two input point clouds to be aligned vertically and also the correspondences estimated a priori as explained here.






                share|improve this answer












                Under registration module, you can find pcl::registration::TransformationEstimation2D<...>. This class expects the two input point clouds to be aligned vertically and also the correspondences estimated a priori as explained here.







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                answered Nov 14 at 23:59









                ozlsn

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