open3Dで点群データをメッシュ化する

実際のところ

import open3d as o3d

import numpy as np

dataset = o3d.data.LivingRoomPointClouds()
pcds = []

pcds.append(o3d.io.read_point_cloud('/root/open3d_data/extract/LivingRoomPointClouds/cloud_bin_1.ply'))
ptCloud = pcds[0]

##近傍の点群をKD木で
ptCloud.estimate_normals(
        search_param=o3d.geometry.KDTreeSearchParamHybrid(radius=0.1, max_nn=30))

# 点群のベクトル方向群を正規化する（点に方向はないので）
ptCloud.orient_normals_consistent_tangent_plane(10)
       
# "ball pivoting"法で表面を構築
distances = ptCloud.compute_nearest_neighbor_distance()
avg_dist = np.mean(distances)
radius = 2*avg_dist   
radii = [radius, radius * 2]
recMeshBPA = o3d.geometry.TriangleMesh.create_from_point_cloud_ball_pivoting(
            ptCloud, o3d.utility.DoubleVector(radii))

#描画
o3d.visualization.draw_plotly(
  [recMeshBPA],
  width=400,
  height=400
)