python fpfh点云配准
时间: 2023-11-10 09:06:16 浏览: 211
icp点云配准代码python
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FPFH是一种点云配准算法,它可以计算点云之间的特征描述符,从而实现点云的配准。下面是使用Pyth实现FPFH点云配准的步骤:\n\1.导入必要的库和模块:\n\```pyth\impor op3 as 3\impor numpy as np\from sklear.neighbors impor NresNeighbors\```\n\2.加载点云数据:\n\```pyth\sour = 3.i.r_poi_clou(\sour.p\")\rg = 3.i.r_poi_clou(\rg.p\")\```\n\3.计算法线:\n\```pyth\sour.stim_normals(search_param=3.geometry.KDTrSearchParamHybri(radius=.1, max_=30))\rg.stim_normals(search_param=3.geometry.KDTrSearchParamHybri(radius=.1, max_=30))\```\n\4.计算FPFH特征描述符:\n\```pyth\sour_fpfh = 3.pipelines.registrati.compu_fpfh_featur(sour, 3.geometry.KDTrSearchParamHybri(radius=.25, max_=100))\rg_fpfh = 3.pipelines.registrati.compu_fpfh_featur(targ, 3.geometry.KDTrSearchParamHybri(radius=.25, max_=100))\```\n\5.找到最近邻点:\n\```pyth\ = NresNeighbors(_neighbors=1)\.fi(np.asarray(targ_fpfh.))\iss, indices = .kighbors(np.asarray(sour_fpfh.))\```\n\6.设置ICP参数并运行ICP:\n\```pyth\hresh = .02\rans_ini = np.asarray([[1, , , ],\ [, 1, , ],\ [, , 1, ],\ [., ., ., 1.]])\reg_p2p = 3.pipelines.registrati.registrati_ip(sour, targ, thresh, trans_ini,\ 3.pipelines.registrati.TransformatiEsimatiPoiToPoi(),\ 3.pipelines.registrati.ICPCvergCriteri(max_iterati=200))\```\n\7.输出配准结果:\n\```pyth\pri(reg_p2p.transformati)\```\n\以上就是使用Pyth实现FPFH点云配准的步骤。需要注意的是,这只是其中一种实现方式,还有其他的实现方式,如使用PCL库等。\n\
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