Game Development Reference
In-Depth Information
•
Map-based
: A 3D map of the surroundings is created and the elements of
a landscape are used as references. For instance, AR applications can use
simultaneous localization and mapping
(
SLAM
) tracking, a technology
that is utilized by autonomous, movable robots. This is one of the most ad-
vanced methods of orientation and navigation in space. It allows us to use
real surroundings, and virtual elements can interact with real-world objects in
a more natural way.
•
Location-based
: This algorithm does not require any graphic markers. It
uses the advantages of GPS (or its competitors), the compass, and accelero-
meter to determine the position and tilt of a device. Usually, such technology
is used to add some virtual features to AR geo-information about real physic-
al objects, such as city landmarks, in order to give the virtual representation
of the information some textual and graphic description, interactive function-
ality, and so on. There are also some interesting massively multiplayer online
game projects based on accurate location detection.
ARisbasedonthreefundamental actions:recognition, tracking,andadaptation. The
system analyzes an image that it gets from the camera and tries to recognize some
important reference points (usually up to 10 can be used, but advanced AR systems
can work with thousands and even tens of thousands of markers). Then it calculates
changes of reference point's coordinates over a specific period of time. These para-
meters are tracking in real time. Then the virtual elements of the scene should be
adapted to those changes of the coordinates. Thus general space parameters of the
virtual objects, as position variable, rotation angles, and scales must be adapted to
the new conditions. Since any shift of a reference point is always compensated by
virtual "anti-shift", the subtraction of vectors gives the illusion that the virtual object is
physically attached to a point in the real world.
The following image illustrates the process of interpretations of a fiducial marker:
The principle is pretty obvious and the mechanics are not so complicated. It centers
around the precision of image recognition algorithms, and the smoothness of the illu-
sion depends directly on them. It is not easy to create such algorithms from scratch
without being an expert in image-processing theories and practices. Nevertheless,
there are some ready-to-use solutions that iOS developers can utilize in their applic-
