Open3d学习计划——高级篇 6（体素化）

点云和三角网格是一种十分灵活的，但是不规则的几何类型。体素网格是通过规则的3D网格来表示的另一种3D几何类型，并且它可以看作是2D像素在3D上的对照物。Open3d中的VoxelGrid几何类型能够被用来处理体素网格数据。

从三角网格中生成

Open3d提供了create_from_triangle_mesh函数能够从三角网格中生成体素网格。它返回一个体素网格，其中所有与三角形相交的网格被设置为1，其余的设置为0。其中voxel_zie参数是用来设置网格分辨率。

print('input')
mesh = o3dtut.get_bunny_mesh()
# fit to unit cube
mesh.scale(1 / np.max(mesh.get_max_bound() - mesh.get_min_bound()), center=mesh.get_center())
o3d.visualization.draw_geometries([mesh])

print('voxelization')
voxel_grid = o3d.geometry.VoxelGrid.create_from_triangle_mesh(mesh,
                                                              voxel_size=0.05)
o3d.visualization.draw_geometries([voxel_grid])

input

voxelization

从点云中生成

也能够使用create_from_point_cloud函数从点云中生成体素网格。如果点云中至少有一个点在体素网格内，则该网格被占用。颜色表示的是该体素中点的平均值。参数voxel_size用来定义网格分辨率。

print('input')
N = 2000
pcd = o3dtut.get_armadillo_mesh().sample_points_poisson_disk(N)
# fit to unit cube
pcd.scale(1 / np.max(pcd.get_max_bound() - pcd.get_min_bound()), center=pcd.get_center())
pcd.colors = o3d.utility.Vector3dVector(np.random.uniform(0,1,size=(N,3)))
o3d.visualization.draw_geometries([pcd])

print('voxelization')
voxel_grid = o3d.geometry.VoxelGrid.create_from_point_cloud(pcd,
                                                            voxel_size=0.05)
o3d.visualization.draw_geometries([voxel_grid])

input

voxelization

包含测试

体素网格也能够用来测试点是否在被占用的网格内。方法check_if_included接受一个(n,3)数组作为输入，返回一个bool类型的数组。

queries = np.asarray(pcd.points)
output = voxel_grid.check_if_included(o3d.utility.Vector3dVector(queries))
print(output[:10])

[True, True, True, True, True, True, True, True, True, True]

体素雕刻

方法create_from_point_cloud和create_from_triangle_mesh只能够在几何体的表面创造体素网格。然而从大量的深度图或者轮廓中雕刻一个体素网格是有可能的。Open3d提供了carve_depth_map和 carve_silhouette方法用于体素雕刻。

下面的代码展示了使用方法，首先从一个几何形状中得到 depthmaps ，之后使用 depthmaps 去雕刻出稠密的体素网格。最后的结果是一个给定形状的填充的体素网格。

def xyz_spherical(xyz):
    x = xyz[0]
    y = xyz[1]
    z = xyz[2]
    r = np.sqrt(x * x + y * y + z * z)
    r_x = np.arccos(y / r)
    r_y = np.arctan2(z, x)
    return [r, r_x, r_y]

def get_rotation_matrix(r_x, r_y):
    rot_x = np.asarray([[1, 0, 0], [0, np.cos(r_x), -np.sin(r_x)],
                        [0, np.sin(r_x), np.cos(r_x)]])
    rot_y = np.asarray([[np.cos(r_y), 0, np.sin(r_y)], [0, 1, 0],
                        [-np.sin(r_y), 0, np.cos(r_y)]])
    return rot_y.dot(rot_x)

def get_extrinsic(xyz):
    rvec = xyz_spherical(xyz)
    r = get_rotation_matrix(rvec[1], rvec[2])
    t = np.asarray([0, 0, 2]).transpose()
    trans = np.eye(4)
    trans[:3, :3] = r
    trans[:3, 3] = t
    return trans

def preprocess(model):
    min_bound = model.get_min_bound()
    max_bound = model.get_max_bound()
    center = min_bound + (max_bound - min_bound) / 2.0
    scale = np.linalg.norm(max_bound - min_bound) / 2.0
    vertices = np.asarray(model.vertices)
    vertices -= center
    model.vertices = o3d.utility.Vector3dVector(vertices / scale)
    return model

def voxel_carving(mesh,
                  output_filename,
                  camera_path,
                  cubic_size,
                  voxel_resolution,
                  w=300,
                  h=300,
                  use_depth=True,
                  surface_method='pointcloud'):
    mesh.compute_vertex_normals()
    camera_sphere = o3d.io.read_triangle_mesh(camera_path)

    # setup dense voxel grid
    voxel_carving = o3d.geometry.VoxelGrid.create_dense(
        width=cubic_size,
        height=cubic_size,
        depth=cubic_size,
        voxel_size=cubic_size / voxel_resolution,
        origin=[-cubic_size / 2.0, -cubic_size / 2.0, -cubic_size / 2.0])

    # rescale geometry
    camera_sphere = preprocess(camera_sphere)
    mesh = preprocess(mesh)

    # setup visualizer to render depthmaps
    vis = o3d.visualization.Visualizer()
    vis.create_window(width=w, height=h, visible=False)
    vis.add_geometry(mesh)
    vis.get_render_option().mesh_show_back_face = True
    ctr = vis.get_view_control()
    param = ctr.convert_to_pinhole_camera_parameters()

    # carve voxel grid
    pcd_agg = o3d.geometry.PointCloud()
    centers_pts = np.zeros((len(camera_sphere.vertices), 3))
    for cid, xyz in enumerate(camera_sphere.vertices):
        # get new camera pose
        trans = get_extrinsic(xyz)
        param.extrinsic = trans
        c = np.linalg.inv(trans).dot(np.asarray([0, 0, 0, 1]).transpose())
        centers_pts[cid, :] = c[:3]
        ctr.convert_from_pinhole_camera_parameters(param)

        # capture depth image and make a point cloud
        vis.poll_events()
        vis.update_renderer()
        depth = vis.capture_depth_float_buffer(False)
        pcd_agg += o3d.geometry.PointCloud.create_from_depth_image(
            o3d.geometry.Image(depth),
            param.intrinsic,
            param.extrinsic,
            depth_scale=1)

        # depth map carving method
        if use_depth:
            voxel_carving.carve_depth_map(o3d.geometry.Image(depth), param)
        else:
            voxel_carving.carve_silhouette(o3d.geometry.Image(depth), param)
        print("Carve view %03d/%03d" % (cid + 1, len(camera_sphere.vertices)))
    vis.destroy_window()

    # add voxel grid survace
    print('Surface voxel grid from %s' % surface_method)
    if surface_method == 'pointcloud':
        voxel_surface = o3d.geometry.VoxelGrid.create_from_point_cloud_within_bounds(
            pcd_agg,
            voxel_size=cubic_size / voxel_resolution,
            min_bound=(-cubic_size / 2, -cubic_size / 2, -cubic_size / 2),
            max_bound=(cubic_size / 2, cubic_size / 2, cubic_size / 2))
    elif surface_method == 'mesh':
        voxel_surface = o3d.geometry.VoxelGrid.create_from_triangle_mesh_within_bounds(
            mesh,
            voxel_size=cubic_size / voxel_resolution,
            min_bound=(-cubic_size / 2, -cubic_size / 2, -cubic_size / 2),
            max_bound=(cubic_size / 2, cubic_size / 2, cubic_size / 2))
    else:
        raise Exception('invalid surface method')
    voxel_carving_surface = voxel_surface + voxel_carving

    return voxel_carving_surface, voxel_carving, voxel_surface

mesh = o3dtut.get_armadillo_mesh()

output_filename = os.path.abspath("../../TestData/voxelized.ply")
camera_path = os.path.abspath("../../TestData/sphere.ply")
visualization = True
cubic_size = 2.0
voxel_resolution = 128.0

voxel_grid, voxel_carving, voxel_surface = voxel_carving(
    mesh, output_filename, camera_path,
    cubic_size, voxel_resolution)

Carve view 001/642
Carve view 002/642
Carve view 003/642
Carve view 004/642
…
Carve view 642/642
Surface voxel grid from pointcloud

print("surface voxels")
print(voxel_surface)
o3d.visualization.draw_geometries([voxel_surface])

print("carved voxels")
print(voxel_carving)
o3d.visualization.draw_geometries([voxel_carving])

print("combined voxels (carved + surface)")
print(voxel_grid)
o3d.visualization.draw_geometries([voxel_grid])

surface voxels
geometry::VoxelGrid with 17215 voxels.

carved voxels
geometry::VoxelGrid with 48370 voxels.

combined voxels (carved + surface)
geometry::VoxelGrid with 50786 voxels.