Project Scenario
A manager of a science museum wishes to create a new exhibit using augmented reality. This exhibit allows the end user to explore the room with a mobile device with planets overlaid into the environment that can be viewed through a virtual tour of the solar system. This exhibit would allow basic interaction between the user and the augmented environment. This exhibit must be easy to set up calibrate and maintain and should be relatively inexpensive.
Project Aims
The goal of this project is to examine and implement the applications of augmented reality in an educational and entertainment context, by producing an application which generates an augmented reality planetarium on a mobile device. This project will be an exploration of the practical applications of various techniques using both vision and motion based augmented reality. This exploration of techniques hopes to produce a hybrid method of implementing augmented reality using both markers and simultaneous localisation and mapping (SLAM) based tracking that is easy for the end user to set up and calibrate. This application will also allow for augmented reality objects to still be tracked even when the marker that spawn the object is partially or totally obscured from the camera’s viewfinder by using the previous scene data and the mobile platforms accelerometer data.
Augmented Reality
Augmented Reality (AR) is a method for integrating computer generated imagery (CGI) with a real world video feed, with the correct pose and perspective. There are several methods to achieve this effect.
- · Camera tracking with fiduciary markers, that can be used to estimate pose based on images
- · Camera tracking with computer vision and natural feature tracking, that calculate pose without markers on the fly
- · GPS tracking
- · Inertial tracking using gyroscopes and accelerometers
- · Tracking using sonar sensors
Example fiduciary marker
All of these methods have advantages and disadvantages with regard to accuracy and computing power required to implement. There have been some applications that use a hybrid of different tracking methods, although these seem few and closed source. The most commonly used method in commercial phone applications is camera tracking with fiduciary markers as it has the best balance between accuracy and computing power required for mobile phones.
AR has been developed since the mid 90s. However due to the cost of custom hardware and tracking software, and the difficulty to calibrate, AR hasn’t seen much commercial use until recently. This is due to commercially available mobile devices with cameras and gyroscopes now being common and the development of several SDKs to aid in the development of AR apps.
ARToolkit Plus
AR Toolkit is one of the oldest augmented reality libraries which use fiduciary markers for pose detection. It is well known and commonly used as it is released under the terms of the GPL. This means a potential design if using this SDK could be integration into the original source code. If ARtoolkit is used in this project the ARtoolkit plus variant the last version of AR Toolkit before it the project that created it became closed source. This is due to this fact AR toolkit has not been officially updated since 2006, although unofficial updates do continue. ARToolkit was originally designed for PC,but as it is open source it is possible to cross compile to mobile platforms however experimentations with the marker tracking on the iPhone showed that it library did not respond well to the sudden disappearance of the marker and left the augment image up on screen for several seconds . Finally AR toolkit plus is incredibly sensitive to the fiduciary being obscured and will cease tracking if only a tiny piece of the fiduciary marker is missing.
Parallel Tracking and Mapping (PTAM)
PTAM is a tracking library that does not use fiduciary markers; instead it uses natural feature tracking to generate pose estimation that can be used for augmented reality.
OpenCV
OpenCV is not an augmented reality fiduciary marker tracking system, but a digital image analysis and processing library. It can be adapted to work as a marker tracking system that allows for 6 degree of freedom. Furthermore it could allow easier integration of further image tracking techniques, and would allow for more flexibility in how the markers and environment are tracked then AR toolkit and if implemented correctly can use more complex fiduciary markers than ARToollit. The primary disadvantage of using this library is that it would probably take longer and require more research to get the basic application operational.
Qualcomm AR SDK
Qualcomm has released an augmented reality SDK for both the android and IPhone platforms. This toolkit whilst not open source is free to use and distribute, and contains many features include in the closed source version of ARToolkit SDK. It also allows for more complicated fiduciary markers than ARToolkit and handles partial obfuscation of the fiduciary. Furthermore this SDK is optimised to work specifically on mobile platforms.
