Split multiple planes using ransac in 3D Pointcloud

Question

How to split multiple planes using ransac in 3D Pointcloud？My code can only split one plane at present.

Right now I am working to do plane segmentation of 3D point cloud data using RANSAC.My code can only split one plane at present. I want to remove one plane after splitting it and continue to split other planes. How can I do this.

`# -*-coding:utf-8 -*-
import os
import open3d as o3d
import numpy as np

test_data_dir = 'D:/test data'
point_cloud_file_name = 'Area6_office_5.pcd'
point_cloud_file_path = os.path.join(test_data_dir, point_cloud_file_name)
# 读取点云
pcd = o3d.io.read_point_cloud(point_cloud_file_path)
# 平面分割
plane_model, inliers = pcd.segment_plane(distance_threshold=0.03,
                                         ransac_n=3,
                                         num_iterations=1000)
# 模型参数
[a, b, c, d] = plane_model
print(f"Plane equation: {a:.2f}x + {b:.2f}y + {c:.2f}z + {d:.2f} = 0")
# 平面内的点
inlier_cloud = pcd.select_by_index(inliers)
inlier_cloud.paint_uniform_color([255.0, 0, 255.0])
# 平面外的点
outlier_cloud = pcd.select_by_index(inliers, invert=True)
# 可视化
o3d.visualization.draw_geometries([inlier_cloud, outlier_cloud],
                                  zoom=0.8,
                                  front=[-0.4999, -0.1659, -0.8499],
                                  lookat=[2.1813, 2.0619, 2.0999],
                                  up=[0.1204, -0.9852, 0.1215])
`

enter image description here

Answer 1

Since you already have outlier_cloud which is the point cloud with the first plane removed. You can easily do the same for outlier_cloud to get the rest planes. For example, try the code below after running your script.

plane_model_2, inliers_2 = outlier_cloud.segment_plane(distance_threshold=0.03,
                                         ransac_n=3,
                                         num_iterations=1000)

# inliner2
inlier_cloud_2 = outlier_cloud.select_by_index(inliers_2)
inlier_cloud_2.paint_uniform_color([1, 0, 1])
# outlier2
outlier_cloud_2 = outlier_cloud.select_by_index(inliers, invert=True)
# visualization
o3d.visualization.draw_geometries([inlier_cloud_2, outlier_cloud_2],
                                  zoom=0.8,
                                  front=[-0.4999, -0.1659, -0.8499],
                                  lookat=[2.1813, 2.0619, 2.0999],
                                  up=[0.1204, -0.9852, 0.1215])

Answer 2

def DetectMultiPlanes(points, min_ratio=0.05, threshold=0.01, iterations=1000):
""" Detect multiple planes from given point clouds

Args:
    points (np.ndarray): 
    min_ratio (float, optional): The minimum left points ratio to end the Detection. Defaults to 0.05.
    threshold (float, optional): RANSAC threshold in (m). Defaults to 0.01.

Returns:
    [List[tuple(np.ndarray, List)]]: Plane equation and plane point index
"""

plane_list = []
N = len(points)
target = points.copy()
count = 0

while count < (1 - min_ratio) * N:
    w, index = PlaneRegression(
        target, threshold=threshold, init_n=3, iter=iterations)

    count += len(index)
    plane_list.append((w, target[index]))
    target = np.delete(target, index, axis=0)

return plane_list

def PlaneRegression(points, threshold=0.01, init_n=3, iter=1000):
    """ plane regression using ransac
    Args:
        points (ndarray): N x3 point clouds
        threshold (float, optional): distance threshold. Defaults to 0.003.
        init_n (int, optional): Number of initial points to be considered inliers in each iteration
        iter (int, optional): number of iteration. Defaults to 1000.
    Returns:
        [ndarray, List]: 4 x 1 plane equation weights, List of plane point index
    """

    pcd = NumpyToPCD(points)

    w, index = pcd.segment_plane(
        threshold, init_n, iter)

    return w, index

the whole code from github