# Advanced Assistive Maintenance Based on Augmented Reality and 5G Networking
## 2 AR for Egocentric Vision  
The first Head-Mounted Displays (HMDs) date back to the 1960s, when the head tracking capability was first introduced by [PERSON] [4]; then their use grew continuously, first in the Virtual Reality (VR) world for networked applications such as DIVE [5] or MASSIVE [6] and then in the 1990s, for the networked AR systems such as Studierstube [7] or Shared Space [8] (further historical details can be found in [9]). Figure 1: The proposed Advanced Assistive Maintenance framework. An AR viewer, equipped with a depth sensor and a thermal camera, sends multi-sensor information over an IEEE 802.11 ac WLAN to a customer-premises equipment (CPE). The CPE is then connected through a 5G link to a Multi-access Edge Computer (MEC) that processes the received data to detect heat-sources and obstacles. Coordinates of detected points are sent back to the helmet and visualized in real-time. The same connection is also used for an interactive video call. Nowadays, we dispose of a wide variety of VR and AR devices, from cheap, smartphone-based ones, such as the papercraft FOV2 GO from the University of Southern California [10], to more advanced and professional devices [11] such as Microsoft HoloLens, Magic Leap One and Google Glass. In addition to assistive maintenance [1,2], AR has proven its effectiveness in a wide range of applications, such as training for high-precision tasks [12], indoor navigation in large buildings (such as hospitals, airports and train stations) [13], education [14], image-guided surgery [15] and telemedicine [16]. Within the different features of AR for assistive maintenance, _telepresence_, i.e., the possibility to interact with a remote specialist along with real and virtual objects, is among the most exciting and requested capabilities. Telepresence can be carried out in different forms, from the old and simplest voice call to the most advanced _telexistence_, where a full holographic representation of the remote assistant is able to interact in real-time with virtual objects in the real scene. Of course, the higher the interaction complexity, the larger the required amount of exchanged data. Furthermore, the transmission latency must be as low as possible to ensure an immersive and realistic interaction. The reasons for an unnatural and, in some cases, disturbing fusion of real and virtual elements in HMDs are to be found in the following: delays between the helmet's movement and the refresh of the virtual scene; oversimplified 3D mesh surfaces; wrong ray-traced illumination of virtual objects. Recent smartglasses, such as Microsoft HoloLens, cope well with these aspects thanks to the integration of the internal Inertial Measurement Unit (IMU) with the on-board processing of multiple cameras and depth-cameras in a Simultaneous Localization and Mapping (SLAM) approach [17]. The user's head position is continuously tracked with high accuracy so that no delay or misplacement in the rendering of virtual objects is noticeable. However, an additional physical cause of disturbing effects is related to the imperfect eyes trick induced by images projected on the holographic lenses. The human visual system allows for the perception of a three-dimensional world from plain and ambiguous stereo images obtained from the eyes. There are different theories on how this is accomplished; one of the most credited is based on the _Cue Theory_[18], where 10 depth cues interact with lighting and scene structure in order to provide a complete three-dimensional understanding [19]:  
* binocular disparity;
* binocular convergence;
* accommodative focus;
* atmospheric haze;
* motion parallax;
* linear perspective and foreshortening;
* occlusion;
* height in the visual field;
* shading;
* texture gradient. AR allows to trick our visual system into merging virtual objects seamlessly with the real environment by acting on some of the aforementioned cues.