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Graduation Project: A point cloud semantic segmentation and VIO based 3D reconstruction method using RGB-D and IMU

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SSVIO

Graduation Project: A point cloud semantic segmentation and VIO based 3D reconstruction method using RGB-D and IMU

Newest result

reconstruction.png

REMEMBER!

Note that the metric of pointcloud is same as the LSB of depth sensor!

The coordinate of camera and world is as follow(Red:X, Blue:Y, Green:Z):

coordinate.png

Requirement

apt install libsuitesparse-dev
  • openni:
apt install libopenni2-dev

Usage

  • Go to {YOUR_DIRECTORY}/SSVIO
  • Run following code
    mkdir build
    cd ./build
    cmake ..
    make
  • After generating bin file, go to {YOUR_DIRECTORY}/SSVIO/bin
  • Run following code

Visual Reconstruction

  • visual reconstruction app:
    ./run_visual_reconstruct

map pointcloud data will be saved at {YOUR_DIRECTORY}/SSVIO/savings/map.pcd

Saving Data

  • photo shooting and data saving app:
    ./run_saving_data

Press "s" to save image and pointcloud at {YOUR_DIRECTORY}/SSVIO/savings

  • Run at {YOUR_DIRECTORY}
    bash ./removedata.sh

to remove all the saved files

Feature matching Pose optimization and Frame jointment

  • feature matching app:
    ./run_feature_match

input saved data num * 2

output matched feature points

  • pose optimization:
    ./run_g2o_optim

input saved data num * 2

output pose and matched feature points

  • frame jointment:
    ./run_frame_jointment

input saved data num * 2

output frame_joint.pcd saved at {YOUR_DIRECTORY}/SSVIO/savings/pointcloud

Visualization

After running ./run_visual_reconstruct, you will see three windows:

  • RGB for RGB image
  • Depth for depth image
  • PointCloud for PointCloud viewer

Press "Esc" at RGB window or press "Ctrl-C" at terminal to stop the program

Bug

  • Use solvepnpRANSAC to filter outliers
  • Jacobian of IMU measure
  • Local g2o optimization error
  • Not orthogonal error

Author

avatar.png

Student from HITSZ Automatic Control NRS-lab

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Graduation Project: A point cloud semantic segmentation and VIO based 3D reconstruction method using RGB-D and IMU

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