Marker-based AR

This type of AR also known as Recognition based AR or Image Recognition is reliant on identification of markers/user defined images; it requires a marker to activate an augmentation. Markers are distinct patterns that cameras can easily recognize and process and are visually independent of the environment around them; they can be paper-based or physical objects that exist in the real world.

Maker-based AR is usually experienced by scanning a marker which triggers an augmented experience (whether an object, text, video or animation) to appear on the device. It usually requires software in the form of an app, which enables users to scan markers from their device using its camera feed.

Some examples of Marker-based AR are:

Maker-less AR

Marker-Less AR offers the most control to the user as it allows the user to choose where they would like to place the content. It also allows real life scale placement of the virtual augmented objects. These AR experiences are highly reliant on smart phone features such as sensors, camera and processors to have the best experiences.

Marker-less AR can be split into:

Location-based AR

Location-based AR due to the easy availability of smartphone features that provide location detection; ties augmentation to a specific place and works by reading data from a device’s camera, GPS, digital compass and accelerometer while predicting where the user is focusing as a trigger to pair dynamic location with points of interest in order to provide relevant data or information. Information and virtual objects are mapped out on specific spots/locations then displayed when a user’s device data matches the location.

The reliability of marker-less AR on positional information gathered from a device’s camera, GPS, digital compass and accelerometer makes it more adaptable than marker-based AR as it does not need an image or object cue to deploy.

Some examples of Location-based AR:

Projection-based AR

Projection AR sometimes also referred to as spatial AR is a method of delivering digital information within a stationary context. It focuses on rendering virtual objects within or on a user’s physical space. It is one of the simplest forms of AR where light is blown onto a surface and the interaction is done by touching the projected surface physically.

In projection AR the user is not limited to any device as virtual objects are integrated directly into the environment; users and target objects are also able to move around the environment within a specified zone, in which both the fixed projector and supporting camera for tracking are placed. Projection-based AR methods may be used to create illusions about depth, position and orientation of an object.

Some examples of Projection-based AR:

Superimposition-based AR

Superimposition AR involves either partial or full replacement of an original view of an object with an augmented view of the same object. In this type of AR object recognition plays a vital role because an app cannot replace an original object with an augmented one if it cannot identify the original object. This type of AR has been popularized by social platforms such as Instagram, Facebook and Instagram using their filters.

Some examples of Superimposition-based AR:

User Defined Marker-less AR

These experiences are characterized by non-mainstream apps built by developers to solve problems in their daily lives or their clients. The content launched is usually custom having user defined interaction points. It involves using the AR libraries and existing technology to achieve different kinds of visualizations and interactions.

Some examples of User Defined Marker-less AR: