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Credit: Shivani Baldwa, Raghav Jethliya, under the guidance of Professor Chuang-Jan-Chang from Ming Chi University of Technology, New Taipei City

Odometry using MOIL LIBRARY genrating 3 Views

We used approach designed in MOIL-Lab , “MOIL SDK- MCUT Omnidirectional Imaging Lab” to extricate the fisheye picture into 6 diverse view as: Front, Left, Right respectively. By utilizing this technique, we made a trajectory of 3 view by the arrangement of fisheye pictures as a source document for odometry.

It means we use source fisheye images and integrate that with MOIL Library and generate 6-view odometry. Before we start this project, we have referred the AVI SINGH blogs and github https://github.com/avisingh599/mono-vo. So, this can be a referenced code before starting monocular visual odometry.

Watch this video for more understanding !!!! (Click on below image)

Watch this video

Calibration Parameter T265 CAMERA:

Focal Length:  618.8560
Center or Principle point: (427, 394)

MOIL LIBRARY PARAMETERS

	md->Config("car", 3, 3,
			427,394, 1, //center
			848, 800, 1.68, // resolution
			0, 0, -24.964, 38.2, -16.956, 183.42 //calibration
	);

Download the MOIL dataset: https://bit.ly/3iq759W

If you want to know how to create dataset refer: https://github.com/Shivani1796/How-to-create-MOIL-Dataset

HOW TO RUN ON TERMINAL

Step 1.Open Terminal

Step 2.

git clone https://github.com/Shivani1796/MonocularVisualOdometry-Using-3Views.git

MOIL SDK DEPENDENCIES

sudo apt update
sudo apt upgrade
sudo apt install build-essential cmake pkg-config
sudo apt install libjpeg-dev libpng-dev libtiff-dev
sudo apt install software-properties-common
sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
sudo apt update
sudo apt install libjasper1 libjasper-dev
sudo apt update
sudo apt install libgtk-3-dev
sudo apt install libatlas-base-dev gfortran
sudo apt install libopencv-dev python-opencv

Step 3.Compile command

    cd MonocularVisualOdometry-Using-3Views
    mkdir build 
    cd build 
    cmake .. 
    make 

Step 4.Run command

	./vo /home/shivani/Documents/mydataset/D5_17-04/poses/D5.txt /home/shivani/Documents/fisheye-test-images/D5/%d.png 3.4 0,0 -10,0 10,0
	

DESCRIPTION:

Argument 1: Ground Truth Data (/home/shivani/Documents/mydataset/D5_17-04/poses/D5.txt)

Argument 2: Image sequence  (/home/shivani/Documents/fisheye-test-images/D5/%d.png)

Argument 3: Zoom Factor (3.4)

Argument 4: Front View angle 

Argument 5: Left View angle

Argument 6: Right View angle

NOTE

  • Change img_path and pose_path to correct image sequences and pose file paths according to your system.
  • Ensure focal length and principal point information is correct .

HOW TO RUN ON ECLIPSE

Please follow the below url to understand how to clone poject on Eclipse

Odometry using Round Path

Odometry using Long path

Odometry using Straight Path

---------------------------------------------------------------------------------------------------------------------------------------------------------------

To use ORB matching for feature points switch branch- "ORB-Matching" or https://github.com/Shivani1796/MonocularVisualOdometry-Using-3Views/tree/ORB-Matching

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This project presents visual odometry by Intel RealSense T265 camera with 3 different views.

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  • C++ 98.9%
  • CMake 1.1%