Augmented reality(AR) systems come in different shapes and forms. AR can be implemented in mobile devices and use GPS information, image recognition, and QR codes to to augment or display specific information over one’s surroundings. AR can also be implemented in various other technologies and environments. Some of these environments include medical training, manufacturing and repair, annotation and visualization, entertainment industry, military training etc.

Jul 18, 2018 - ar_markers. Detection of hamming markers for OpenCV written in python. Originally written by Max Brauer: github. All I did was clean up some.

To avoid limiting AR to a specific technology, Azuma (1997) proposes that AR system should have the following characteristics in order to be considered an AR system: • Combines real and virtual • Interactive in real time • Registered in 3D Most of the experiments and projects posted on this blog will focus on desktop and Web AR based AR system. AR fiduciary markers are objects used in the field of view of an imaging system as points of reference of measure. These markers are used in AR so that the objects can be recognized in images of the scene. There is a good online marker generator located at: To build an Augmented Reality system based on a fiduciary marker, you will need the following: • Marker or a pattern it two versions: printed as seen in Figure 1, and.patt file store in your computer. • Camera (connected to the computer) • Computer with running AR software • Output device: Computer monitor, projector or AR glasses. So this is how it works: • You will prepare pattern files in advance.

You can make your pattern file and print it yourself or use some of the available. You can also download two commonly available and markers. Print the PDF file, cut it out with the scissors and have it ready. You will use.patt file later to connect it to a 3D model, image or a movie clip.

• Make sure you have the camera connected to the computer. We are using Logitech Pro 9000 which works very well with. • You will need a computer with some sort of AR software on it. Since we don’t have the time nor personnel to code our own, we are using commercially available. BuildAR also has a which works very well. The only difference between the two is that Pro version has slightly better tracking and the ability to add images and video clips to name a few.When you start the AR software on your PC, you will have to: • Add markers or.patt files that correspond to the printed pattern (Hiro and Kanji) • Assign 3D model to the marker • Specify the input camera If everything is connected correctly, you should be able to see objects (3D files) augmented over the marker live on your output device of choice (monitor, projector or AR glasses). Bibliography R.

Azuma, Presence: Teleoperators and Virtual Environments, pp. 355–385, August 1997.

Purpose This project was for a robotics/computer vision I taught Spring 2018. I wanted something simple enough we could go through the code and they could understood how it worked. I also taught them OpenCV, so I wanted something written in that.

Eventually we made “street signs” and the students drove Roomba robots around on these “strees” (ok, really it was 3 inch wide black tape for the roads). When they detected an intersection, they used a camera to read the street sign (ar marker) and it told them to: go straight, turn left, or turn right. Sometimes it isn’t as robust as I would like, so you may have to move the target around before it gets recognized. Usage There are two helper scripts: • ar_markers_generate.py to generate the markers. Do ar_markers_generate.py --help to see the options • ar_markers_scan.py to scan the marker. Once you have created and printed out a marker, hold the marker in front of your camera.

You will see a blue border around the marker, (if detected) and a green number, showing the ID the marker represents. Or use in a program like: #!/usr/bin/env python from __future__ import print_function import cv2 from ar_markers import detect_markers if __name__ == '__main__': print ( 'Press 'q' to quit' ) capture = cv2. VideoCapture ( 0 ) if capture. IsOpened (): # try to get the first frame frame_captured, frame = capture. Read () else: frame_captured = False while frame_captured: markers = detect_markers ( frame ) for marker in markers: marker.

Highlite_marker ( frame ) cv2. Imshow ( 'Test Frame', frame ) if cv2. WaitKey ( 1 ) & 0xFF == ord ( 'q' ): break frame_captured, frame = capture.

Read () # When everything done, release the capture capture. Release () cv2.

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DestroyAllWindows (). BSD License Copyright (c) 2007, Max Brauer All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1.