Image or object recognition and 3D Object Tracking in Augmented Reality is not a new concept and is, or has been, already enabled mainly by visual markers.Visual markers have been widely used in existing AR applications in last years. In most of these applications, the performance of an AR system depends highly on the tracking method for visual marker detection, pose estimation, and so depending on the particular application. The visual marker’s design can differ from one to another. But the use of these visual markers limit the interactivity and are constrained to a range of photos or objects encapsulated within a border to create the marker. Therefore, in order to use this approach, these visual marks have to be printed previously and also be kept for future uses. Unlike in the marker-based Augmented reality systems, in markerless augmented reality systems any part of the real environment may be used as a target that can be tracked in order to place virtual objects.
An example of AR using visual markers.
With the new advances in mobile technologies, both in hardware and software, new markerless approaches like the ones based on natural features, broke into the Augmented Reality world, not only allowing to use real objects as a target instead of these old and ugly markers, but also overcome some of their limitations.
In order to perform the object tracking, markerless augmented reality systems rely in natural features instead of fiducial marks. Therefore, there are no ambient intrusive markers which are not really part of the environment. Furthermore, markerless augmented reality counts on specialized and robust trackers already available. Another advantage of the markerless systems is the possibility of extracting from the environment characteristics and information that may later be used by them. However, among the disadvantages we can consider for markerless augmented reality systems is that tracking and registration techniques become more complex.
An example of Markerless AR (MAR).
Techniques developed for online monocular markerless augmented reality systems rely in natural features of the image or object to be tracked, like the edges, corners, or textures. In the next image, it is shown a markerless system working at our LABs. In the image can be seen how natural image features are taken in order to do the classification and the tracking.
After having shown some of the main differences between them, we can consider that markerless augmented reality systems are a better option for final applications, because they use normal images or objects as targets and they are no invasive like marker-based systems.