RGBD integration

Open3D implements a scalable RGBD image integration algorithm. The algorithm is based on the technique presented in [Curless1996] and [Newcombe2011]. In order to support large scenes, we use a hierarchical hashing structure introduced in Integrater in ElasticReconstruction.

# src/Python/Tutorial/Advanced/rgbd_integration.py

from py3d import *
from trajectory_io import *
import numpy as np

if __name__ == "__main__":
    volume = ScalableTSDFVolume(voxel_length = 4.0 / 512.0,
            sdf_trunc = 0.04, with_color = True)

    for i in range(len(camera_poses)):
        print("Integrate {:d}-th image into the volume.".format(i))
        color = read_image("../../TestData/RGBD/color/{:05d}.jpg".format(i))
        depth = read_image("../../TestData/RGBD/depth/{:05d}.png".format(i))
        rgbd = create_rgbd_image_from_color_and_depth(color, depth,
                depth_trunc = 4.0, convert_rgb_to_intensity = False)
        volume.integrate(rgbd, PinholeCameraIntrinsic.prime_sense_default,
                np.linalg.inv(camera_poses[i].pose))

    print("Extract a triangle mesh from the volume and visualize it.")
    mesh = volume.extract_triangle_mesh()
    mesh.compute_vertex_normals()
    draw_geometries([mesh])

Read trajectory from .log file

camera_poses = read_trajectory("../../TestData/RGBD/odometry.log")

This tutorial uses function read_trajectory to read a camera trajectory from a .log file. A sample .log file is as follows.

# src/test/TestData/RGBD/odometry.log
0   0   1
1   0   0   2
0   1   0   2
0   0   1 -0.3
0   0   0   1
1   1   2
0.999988  3.08668e-005  0.0049181  1.99962
-8.84184e-005  0.999932  0.0117022  1.97704
-0.0049174  -0.0117024  0.999919  -0.300486
0  0  0  1
:

TSDF volume integration

volume = ScalableTSDFVolume(voxel_length = 4.0 / 512.0,
        sdf_trunc = 0.04, with_color = True)

for i in range(len(camera_poses)):
    print("Integrate {:d}-th image into the volume.".format(i))
    color = read_image("../../TestData/RGBD/color/{:05d}.jpg".format(i))
    depth = read_image("../../TestData/RGBD/depth/{:05d}.png".format(i))
    rgbd = create_rgbd_image_from_color_and_depth(color, depth,
            depth_trunc = 4.0, convert_rgb_to_intensity = False)
    volume.integrate(rgbd, PinholeCameraIntrinsic.prime_sense_default,
            np.linalg.inv(camera_poses[i].pose))

Open3D provides two types of TSDF volumes: UniformTSDFVolume and ScalableTSDFVolume. The latter is recommended since it uses a hierarchical structure and thus supports larger scenes.

ScalableTSDFVolume has several parameters. voxel_length = 4.0 / 512.0 means a single voxel size for TSDF volume is \(\frac{4.0m}{512.0} = 7.8125mm\). Lowering this value makes a high-resolution TSDF volume, but the integration result can be susceptible to depth noise. sdf_trunc = 0.04 specifies truncation value for signed distance function (SDF). When with_color = True, color is also integrated as part of the TSDF volume. The color integration is inspired by PCL.

Extract a mesh

Mesh extraction uses the marching cubes algorithm [LorensenAndCline1987].

print("Extract a triangle mesh from the volume and visualize it.")
mesh = volume.extract_triangle_mesh()
mesh.compute_vertex_normals()
draw_geometries([mesh])

Outputs:

../../_images/integrated.png