• Overview
  • Tag Detection
  • Image Superimposition
  • 3D Projecttion
• License
• Team Members
• Dependencies
• Install Dependencies
• Run
• Output

• The project is divided into 3 parts: AR-Tag detection, superimposition of an image onto to the tag, and drawing a cuboid onto the tag.
• OpenCV methods such as find-homography and warp-perspective have not been used to develop any part of the project.
• The input and output of the project are video files.
• Ideally, all video formats that are supported by the OpenCV library should be supported by the project. We have only tested the code with the MP4 format.
• Output of the project is a video, in AVI format, that combines all the 3 parts of the project.

• OpenCV methods such as findContours, contourArea, and approxPolyDP have been used to detect contours within an image.
• Among the various contours found from the image, ar-tags were found by restricting our search to contours with closed regions of 4 points.
• The output can be seen below in Figure 1 for single as well as multiple tags.

Figure 1 - Stages of tag detection

• Methods to find homography and warp images were developed to warp the image in Figure 2 into the video frame.
• The final output can be seen in Figure 3.

Figure 2 - Image for superimposition

Figure 3 - Superimposition of image on single and multiple AR Tags

• Reference 3D points were taken, then new points were found using projectionPoints method of OpenCV and finally drawContours was used to draw the cube on the video frame.
• 3D projection can be seen in Figure 4.

Figure 4 - 3D-Projection of cuboid on single and multiple AR Tags

• The project is developed under the BSD 3-Clause license to comply with the standard license of the OpenCV library.

• Umang Rastogi - Robotics graduate student at UMD interested in working in the autonomous vehicle industry
• Sayani Roy - UMD Robotics Graduate student interested in medical robotics
• Prateek Bhargava - UMD Robotics Graduate student interested in space robotics

• Python3
• Python3-tk
• Python3 Libraries: Opencv-python and Numpy

• Install Python3, Python3-tk, and the necessary libraries: (if not already installed)

sudo apt install python3 python3-tk
pip3 install opencv-python numpy

• Check if your system successfully installed all the dependencies
• Open terminal using Ctrl+Alt+T and enter python3
• The terminal should now present a new area represented by >>> to enter python commands
• Now use the following commands to check libraries: (Exit python window using Ctrl+Z if an error pops up while running the below commands)

import tkinter
import cv2
import numpy

• Extract the compressed folder onto your system
• Go into the project directory
• Open a terminal window by right-clicking on empty space within the folder and then click Open in Terminal and run the following commands:

cd Code/
python3 main.py path/input-file-name.mp4 path/output-file-name.avi

• For instance:

python3 main.py videos/Tag0.mp4 videos/output_tag0.avi

• Note that the program takes 2 input arguments to run: location of the input video file and destination to store the output video

• Checkout this link to go to the google drive folder with all our final video outputs.
• Please note that each video contains output for all three parts of the project, i.e., tag detection, image superimposition, and draw 3D cube on the tag.
• Output has been generated for each provided file, i.e., from Tag0.mp4 to multipleTags.mp4.
• A sample of the final output can be seen in Figure 5.

Figure 5 - Final output on multiple AR Tags