# Deep-Learning-Incorporated Augmented Reality Application for Engineering Lab Training
## 2 Overview of Deep Learning and Augmented Reality
### Augmented Reality
#### 2.2.2 Marker-Less AR  
Marker-less AR is more versatile than marker-based AR. It interacts with the real object without the need for pre-defined markers but leaves the freedom to the user. This allows the user, for example, to position a virtual object anywhere on a real object. Users can experiment with different styles and locations digitally without having to move anything in their immediate surroundings [36]. Marker-less AR collects data from the device hardware such as a camera, a GPS, a digital compass, and an accelerometer for the AR program to function. Marker-less AR applications rely on computer vision algorithms to distinguish objects, and they can function in the real world without specific markers [37; 38]. There are four types of marker-less AR discussed as follows:  
1. _Location-based AR_: In this type of AR, simultaneous localization and mapping (SLAM) technology is used to track the user's location as the map is generated and updated on the user's mobile device [39]. To display AR content in the physical environment, the user must detect a surface with a mobile device [40; 41]. As an example, the world-famous AR-based game app, Pokemon Go, uses SLAM technology that allows its users to battle, navigate, and search for 3D interactive objects based on their geographical locations [42].
2. _Superimposition-based AR_: Superimposition-based AR applications can provide an additional view along with the original view of the object. Object recognition is required to determine the type of object to partially or completely replace an object in the user's environment with a digital image [43; 44]. Using HoloLens glasses, surgeons can superimpose images previously gathered through scanners or X-rays on the patient's body during the operation. They can anticipate potential problems using this approach.
3. _Projection-based AR_: Projection-based AR (also known as projection mapping and augmented spatial reality) is a technique that does not require the use of head-mounted or hand-held devices. This method allows augmented information to be viewed immediately from a natural perspective. Using projection mapping, projection-based  
Figure 1: Types of augmented reality.  
AR turns an uneven surface into a projection screen. This method allows for the creation of optical illusions [45].
* _Outlining-based AR_: This type of AR employs image recognition to create contours or forms and highlight components of the real world using special cameras. It is used by human eyes to designate specific items with lines to make situations easier. Vuforia's Model Target is an example of outlining-based AR. Vuforia is a platform that enables developers to quickly incorporate AR technology into their applications. Model Targets allow apps to recognize and track real-world objects based on their shape [46].  
In our project, we built a superimposition-based AR app. We built user interfaces on top of lab equipment, allowing step-by-step instructions to be incorporated into the application for users to understand and learn how to use specific equipment. Using AR technology, immersive experiences are created in a variety of ways. It does, however, have some limitations such as the inability to recognize multiple objects at once. On the other hand, DL models show high performances in recognizing multiple objects at the same time. Integrating AR apps with DL models will help trigger specific AR scenarios based on objects being aimed at with a camera and allow an AR scenario to perform a single tracking without decreasing mobile device performance.