ETSI GS ARF 003 V2.1.1 (2024-10)

Augmented Reality Framework (ARF); AR framework architecture

RGS/ARF-003v.2.1.1

General Information

• Status: Not Published
• Technical Committee: ARF - Augmented Reality Framework
• Current Stage: 12 - Citation in the OJ (auto-insert)
• Due Date: 28-Oct-2024
• Completion Date: 18-Oct-2024

Standards Content (Sample)

GROUP SPECIFICATION
Augmented Reality Framework (ARF);
AR framework architecture
Disclaimer
The present document has been produced and approved by the Augmented Reality Framework (ARF) ETSI Industry
Specification Group (ISG) and represents the views of those members who participated in this ISG.
It does not necessarily represent the views of the entire ETSI membership.

2 ETSI GS ARF 003 V2.1.1 (2024-10)

Reference
RGS/ARF-003v.2.1.1
Keywords
API, architecture, augmented reality, context
capturing and analysis, framework, model,
real time
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3 ETSI GS ARF 003 V2.1.1 (2024-10)
Contents
Intellectual Property Rights . 6
Foreword . 6
Modal verbs terminology . 6
1 Scope . 7
2 References . 7
2.1 Normative references . 7
2.2 Informative references . 7
3 Definition of terms, symbols and abbreviations . 8
3.1 Terms . 8
3.2 Symbols . 9
3.3 Abbreviations . 9
4 Architecture Overview . 10
4.1 Global Architecture . 10
4.2 Functional Architecture . 11
5 Functions and subfunctions of the functional architecture . 12
5.1 World Capture . 12
5.1.1 Introduction. 12
5.1.2 Positioning . 13
5.1.3 Orientation and Movement . 13
5.1.4 Visual . 13
5.1.5 Audio . 14
5.2 World Analysis . 14
5.2.1 Introduction. 14
5.2.2 AR Device Relocalization . 14
5.2.3 AR Device Tracking . 14
5.2.4 Object Recognition & Identification . 14
5.2.5 Object Relocalization . 15
5.2.6 Object Tracking . 15
5.2.7 3D Mapping . 15
5.3 World Storage . 15
5.3.1 Introduction. 15
5.3.2 World Representation . 15
5.3.3 Relocalization Information Extraction . 16
5.3.4 Recognition & identification Information Extraction . 16
5.3.5 Object 3D Segmentation . 17
5.3.6 Scene Meshing . 17
5.4 Asset Preparation . 17
5.4.1 Introduction. 17
5.4.2 Synthetic Content . 17
5.4.3 AV content . 17
5.4.4 Object Behaviour . 17
5.4.5 Scenario . 18
5.4.6 Report Evaluation . 18
5.5 External Application Support . 18
5.6 AR Authoring . 18
5.6.1 Introduction. 18
5.6.2 Content Conversion . 18
5.6.3 Content Optimization . 19
5.6.4 AR Scene Compositing . 19
5.6.5 Content Packaging . 19
5.6.6 Content Hosting . 19
5.7 User Interactions . 19
5.7.1 Introduction. 19
5.7.2 3D Gesture . 19
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5.7.3 Tactile . 20
5.7.4 Gaze . 20
5.7.5 Vocal . 20
5.7.6 Biometric . 20
5.8 Scene Management. 20
5.8.1 Introduction. 20
5.8.2 Interaction Technique . 20
5.8.3 Virtual Scene Update . 21
5.8.4 Content Unpackaging . 21
5.8.5 AR Experience Reporting . 21
5.9 3D Rendering . 21
5.9.1 Introduction. 21
5.9.2 Video . 22
5.9.3 Audio . 22
5.9.4 Haptic . 22
5.10 Rendering Adaptation . 22
5.10.1 Introduction. 22
5.10.2 Video see-through . 22
5.10.3 Optical see-through . 22
5.10.4 Projection-based . 22
5.10.5 Audio . 23
5.10.6 Haptics . 23
5.11 Transmission . 23
5.11.1 Introduction. 23
5.11.2 Security . 23
5.11.3 Communications . 23
5.11.4 Service Conditions . 23
6 Reference Points of the Functional Architecture . 24
6.1 Introduction . 24
6.2 Reference point "Sensors for World Analysis AR1" . 24
6.3 Reference point "Sensor Data for Scene Management" AR2 . 25
6.4 Reference Point "External Communications" AR3 . 25
6.5 Reference Point "User Interactivity" AR4 . 26
6.6 Reference Point "Rendered Scene" AR5 . 26
6.7 Reference Point "Rendering Performances" AR6 . 26
6.8 Reference Point "Scene Representation" AR7 . 27
6.9 Reference Point "Pose" AR8 . 27
6.10 Reference Point "Recognized or Identified Object" AR9. 27
6.11 Reference point "World Representation Update" AR10 . 27
6.12 Reference Point "Relocalization Information" AR11 . 28
6.13 Reference Point "Recognition & Identification Information" AR12 . 28
6.14 Reference Point "Scene Objects" AR13 . 29
6.15 Reference Point "AR Session Reports" AR14 . 29
6.16 Reference Point "3D Objects of World ARA" AR15 . 29
6.17 Reference Point "World Anchors" AR16 . 30
6.18 Reference Point "Reference Objects" AR17 . 30
6.19 Reference Point "Content export" AR18 . 30
6.20 Reference Point "3D Objects of World SM" AR19 . 31
7 Use case implementation samples (informative) . 31
7.1 Try before buying with AR . 31
7.1.1 Use case description. 31
7.1.2 Use case implementation . 32
7.2 Maintenance Support . 33
7.2.1 Use case description. 33
7.2.2 Use case implementation . 35
7.3 Manufacturing procedure . 36
7.3.1 Use case description. 36
7.3.2 Use case implementation . 37
7.4 Collaborative design review . 40
7.4.1 Use case description. 40
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7.4.2 Use case implementation . 41
7.5 Factory inspection based on an ARCloud . 43
7.5.1 Use case description. 43
7.5.2 Use case implementation . 44
7.6 Usability Evaluation of Virtual Prototypes . 47
7.6.1 Use case description. 47
7.6.2 Use case implementation . 48
History . 51

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Intellectual Property Rights
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Foreword
This Group Specification (GS) has been produced by ETSI Industry Specification Group (ISG) Augmented Reality
Framework (ARF).
The ISG ARF shares the following understanding for Augmented Reality: Augmented Reality (AR) is the ability to mix
in real-time spatially-registered digital content with the real world. The present document specifies a functional
reference architecture for AR solutions.
Modal verbs terminology
In the present document "shall", "shall not", "should", "should not", "may", "need not", "will", "will not", "can" and
"cannot" are to be interpreted as described in clause 3.2 of the ETSI Drafting Rules (Verbal forms for the expression of
provisions).
"must" and "must not" are NOT allowed in ETSI deliverables except when used in direct citation.

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1 Scope
The present document specifies a functional reference architecture for AR components, systems and services. The
structure of this architecture and the functionalities of its components have been derived from a collection of use cases
ETSI GR ARF 002 [i.3] and an overview of the current landscape of AR standards ETSI GR ARF 001 [i.4].
The present document introduces the characteristics of an AR system and describes the functional building blocks of the
AR reference architecture and their mutual relationships. The generic nature of the architecture is validated by mapping
the workflow of several use cases to the components of this framework architecture.
2 References
2.1 Normative references
References are either specific (identified by date of publication and/or edition number or version number) or
non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the
referenced document (including any amendments) applies.
Referenced documents which are not found to be publicly available in the expected location might be found at
https://docbox.etsi.org/Reference/.
NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee
their long term validity.
The following referenced documents are necessary for the application of the present document.
Not applicable.
2.2 Informative references
References are either specific (identified by date of publication and/or edition number or version number) or
non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the
referenced document (including any amendments) applies.
NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee
their long term validity.
The following referenced documents are not necessary for the application of the present document but they assist the
user with regard to a particular subject area.
[i.1] Ronald T. Azuma: "A survey of augmented reality", in Presence: Teleoperators & Virtual
Environments, 1997.
[i.2] Paul Milgram, H. Takemura, A. Utsumi, F. Kishino: "Augmented Reality: A class of displays on
the reality-virtuality continuum", in Proceedings of Telemanipulator and Telepresence
Technologies, 1994.
[i.3] ETSI GR ARF 002 (V1.1.1): "Augmented Reality Framework (ARF) Industrial use cases for AR
applications and services".
[i.4] ETSI GR ARF 001 (V1.1.1): "Augmented Reality Framework (ARF); AR standards landscape".
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3 Definition of terms, symbols and abbreviations
3.1 Terms
For the purposes of the present document, the following terms apply:
Augmented Reality (AR): ability to mix in real-time spatially-registered digital content with the real world
NOTE: This definition is based on the work of Azuma [i.1] and Milgram [i.2].
AR anchor: coordinate system related to an element of the real world on which virtual content stays spatially-registered
NOTE: AR anchors help users to maintain the perception that static virtual content appears to stay at the same
position and orientation in the real world.
AR application: software designed by using several AR components to perform a group of coordinated functions,
tasks, or activities for the benefit of the user who is experiencing augmented reality
AR component: hardware or software that provides application-oriented computing functions and supports
interoperability when connected with other components of the AR system
AR device: hardware that provides one or more functions offering an augmented reality experience to one or several
users
AR experience: real time perception of the mixture of the real world and spatially-registered digital content by user
senses
AR system: combination of hardware and software that delivers an AR experience
AR scene: information describing the interactive content contributing to an augmented reality experience
Building Information Modeling (BIM): process supported by various tools and technologies involving the generation
and management of digital representations of physical and functional characteristics of places
descriptor extraction: task consisting in extracting differentiating characteristics of a detected feature
feature detection: task consisting in detecting specific information from a given signal
function: collection of functionalities
object recognition: task consisting in finding and identifying objects
EXAMPLE: Recognition may be performed on an image, a video sequence, or an audio stream.
object tracking: task consisting in locating an object over time
EXAMPLE 1: A 2D tracking consists in locating an object in a sequence of images.
EXAMPLE 2: A 3D tracking consists in locating an object in a 3D space from a sequence of images or an audio
signal.
point cloud: set of data points in space defined in a common coordinate system
EXAMPLE: A 3D point cloud is a set of data points in a 3D space.
pose: position and orientation of an object, defined in a given coordinate system
EXAMPLE: The camera pose defined in a world coordinate system.
pose estimation: task of determining the pose of an object
Product Lifecycle Management (PLM): process of managing the entire lifecycle of a product from inception through
engineering, design, and manufacture to service and disposal of manufactured products
random forest: learning method based on a multitude of decision trees used for classification or regression tasks
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reference point: point located at the interface of two non-overlapping functions and representing interrelated
interactions between those functions
visual bag of words: simplified representation using image features as words for image retrieval task
visual descriptor: characteristics of a visual feature
NOTE: A descriptor is based on elementary characteristics such as the shape, the colour, the texture or the motion
of the feature itself and its neighbourhood in the image.
EXAMPLE: SIFT, SURF, BRIEF, ORB, BRISK, FAST, etc.
visual feature: information representing an element of an image
NOTE: The feature are generally primitive geometric elements (points, edges, lines, polygons, colours, textures,
or any shapes) used to characterize an image.
EXAMPLE: Key points, edges, blobs.
3.2 Symbols
Void.
3.3 Abbreviations
For the purposes of the present document, the following abbreviations apply:
AI Artificial Intelligence
AR Augmented Reality
AV AudioVisual
BIM Building Information Modeling
BRIEF Binary Robust Independent Elementary Features
CAD Computer-Aided Design
DoF Degree of Freedom
GNSS Global Navigation Satellite System
GPS Global Positioning System
GPU Graphic processing Unit
GUI Graphical User Interface
ID Identifier
IMU Inertial Measurement Unit
IP Internet Protocol
Li-Fi™ Light Fidelity
ORB Oriented FAST and Rotated Brief
PLM Product Lifecycle Management
RFID Radio-Frequency Identification
RGB Red, Green, Blue
RGB-D Red, Green, Blue and Depth
SIFT Scale-Invariant Feature Transform
SURF Speeded Up Robust Features
TPU Tensor Processing Unit
UWB Ultra-WideBand
VPU Vision Processing Unit
VR Virtual Reality ®
Wi-Fi Wireless Fidelity
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4 Architecture Overview
4.1 Global Architecture
An AR system is based on a set of hardware and software components as well as data describing the real world and
virtual content. Figure 1 presents a global overview of an AR system architecture. The architecture diagram is
structured in three layers, in the upper part the hardware, in the middle the software, and in the lower part the data:
• Hardware layer:
- Tracking Sensors: These sensors aim to localize (position and orientation) the AR system in real-time
in order to register virtual contents with the real environment. Most of AR systems such as smartphones,
tablets or see-through glasses embed at least one or several vision sensors (generally monochrome or
RGB cameras) as well as an inertial measurement unit and a GPS. However, specific and/or recent
systems use complementary sensors such as dedicated vision sensors (e.g. depth sensors and event
™ ®
cameras), or exteroceptive sensors (e.g. Infrared/laser tracking, Li-Fi and Wi-Fi ).
- Processing Units: Computer vision, machine learning-based inference as well as 3D rendering are
processing operations requiring significant computing resources optimized thanks to dedicated processor
architectures (e.g. GPU, VPU and TPU). These processing units can be embedded in the device, can be
remote and/or distributed.
- Rendering Interfaces: Virtual content requires interfaces to be rendered to the user so that he or she can
perceive them as part of the real world. As each rendering device has its own characteristics, the signals
generated by the rendering software generally need to be transformed in order to adapt them to each
specific rendering hardware.
• Software layer:
- Vision Engine: This software aims to mix the virtual content with the real world. It consists of localizing
(position and orientation) the AR device relative to the real world reference, localizing specific real
objects relatively to the AR device, reconstructing a 3D representation of the real world or analysing the
real world (e.g. objects detection, segmentation, classification and tracking). This software component
essentially uses vision sensors signals as input, but not only (e.g. fusion of visual information with
inertial measurements or initialization with a GPS), it benefits from the hardware optimization offered by
the various dedicated processors embedded in the device or remote, and will deliver to the rendering
engine all information required to adapt the rendering for a consistent combination of virtual content with
the real world.
- 3D Rendering Engine: This software maintains an up-to-date internal 3D representation of the virtual
scene augmenting the real world. This internal representation is updated in real-time according to various
inputs such as user's interactions, virtual objects behaviour, the last user viewpoint estimated by the
Vision Engine, an update of the World Knowledge to manage for example occlusions between real and
virtual elements, etc. This internal representation of the virtual content is accessible by the renderer
(e.g. video, audio or haptic) which produces thanks to dedicated hardware (e.g. Graphic Processing unit)
data (e.g. 2D images, sounds or forces) ready to be played by the Rendering Interfaces (e.g. screens,
headphones or a force-feedback arm).
• Data layer:
- World Knowledge: This World Knowledge represents the information either generated by the Vision
Engine or imported from external tools to provide information about the real world or a part of this world
(CAD model, markers, etc.). This World Knowledge corresponds to the digital representation of the real
space used for different usages such as localization, world analysis, 3D reconstruction, etc.
- Interactive Contents: These Interactive Contents represent the virtual content mixed to the perception
of the real world. These contents can be interactive or dynamic, meaning that they include both 3D
contents, their animations, their behaviour regarding input events such as user's interactions. These
Interactive Contents could be extracted from external authoring tools requiring to adapt original content
to AR application (e.g. 3D model simplification, fusion, and instruction guidelines conversion).
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Figure 1: Global overview of the architecture of an AR system
4.2 Functional Architecture
Figure 2 shows the functional architecture specified by the present document addressing both fully embedded
AR systems and implementations spread over IP networks in a scalable manner. Logical functions are shown as named
boxes that may be nested in cases where a high-level function is composed of several subfunctions. The logical
functions are connected by reference points. A reference point in a functional architecture is located at the conjunction
of two non-overlapping functions and represents the interrelated interactions between those functions. A reference point
allows a framework to aggregate those abilities that one function provides towards another function. In a practical
deployment each of these reference points can be realized by a physical interface that conveys information between the
connected subfunctions in a unidirectional or bidirectional way using a specified protocol. Depending on the
deployment scenario and the applications that needs to be supported, multiple logical subfunctions can also be
combined in one deployable unit. All of these subfunctions can either be deployed on the device that also presents the
AR implementation or they can be provided via cloud technology.
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Figure 2: Diagram of the functional reference architecture
5 Functions and subfunctions of the functional
architecture
5.1 World Capture
5.1.1 Introduction
This function delivers information relevant for the localization of the AR device or real objects, or for analysing the
environment of the application. AR systems can embed various sensors aiming at better understanding the real
environment as well as the pose (position and orientation) of the AR system or of real objects in this environment
required to provide an accurate registration of virtual objects on the real world. The following subfunctions can address
different kinds of sensors.
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5.1.2 Positioning
This subfunction shall deliver the location of an AR device and may also deliver its orientation relatively to a coordinate
reference system. The coordinate reference system shall be defined in relation to a reference in the real world and there
shall be a mechanism to temporally synchronize this information with other World Capture subfunctions.
NOTE 1: The coordinate reference system can be related to the earth (global geo-positioning system), a factory, a
room, an object, the positioning system itself, etc.
NOTE 2: GNSS are the most commonly used means to provide a position, but other solution such as beacons,
Li-Fi™, UWB or other radio technologies can also provide a position or even an orientation of an AR
system device.
5.1.3 Orientation and Movement
This subfunction shall deliver information about the movement or the orientation of the device that is providing the AR
experience. This information shall be defined in a given coordinate system and there shall be a mechanism to
temporally synchronize this information with other World Capture subfunctions.
NOTE 1: This subfunction can make use of the information provided by the subfunction Positioning.
NOTE 2: Inertial measuring can provide information about the movement and orientation of the device with a high
frequency (~1 000 captures per seconds) which is useful to interpolate intermediate device poses between
two vision-based pose estimations or when vision-based pose estimation fails.
5.1.4 Visual
This subfunction applies to AR systems making use of cameras (e.g. RGB, depth or event-based) which support the
device providing AR experience. The cameras can be built into the device (interoceptive capture) or positioned outside
the device (exteroceptive capture).
This subfunction shall deliver streaming video/event or still pictures to be used by the World Analysis function.
This subfunction should also deliver information about camera parameters relevant for the application (e.g. focal
lengths, pixel size, principal point, image size, global or rolling shutter, distortion parameters, timing information and
camera range) and in the case where the application uses several vision sensors, their relative positions and orientations.
Different kind of visual sensors can be addressed by this subfunction:
• RGB cameras make use of a photo-sensitive sensors by which coloured images are acquired. Colours are
represented by an additive combination of the three primary colours red, green and blue.
• Depth cameras produce two-dimensional images that contain information about the distance to points of a
scene from a given specific point. Several technologies can be used to achieve such information (e.g.
stereoscopic triangulation, light patterns). In many cases, a depth camera can also provide a cloud of points
defined in the coordinate system of the sensor.
• RGB-D cameras produce both two-dimensional images captured by a RGB camera and two-dimensional
images captured by a depth sensor. For this reason, RGB-D cameras provide both camera and depth sensor
interfaces. But, since an RGB-D camera is usually composed of two separate sensors, an RGB camera and a
depth sensor (time of flight, structured-lights-based, stereoscopic, etc.), the raw images from the two sensors
are not aligned. For this reason, RGB-D sensors offer complementary interfaces to match RGB and depth
images.
• Event-based cameras measure the changes in brightness and colour in a scene over a given time period and
allows the detection of movement of objects within the scene.
• Infrared cameras measure the infrared radiation of an object and maps the measured wavelength range into a
picture using pseudo-colours.
• Laser trackers are used to measure the distance between such devices and objects that reflect laser pulses sent
out by the tracker. Often, these measurements are mapped into a local coordinate system.
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5.1.5 Audio
This subfunction applies to AR systems making use of microphones which support the device providing AR experience.
The microphone can be built into the device (interoceptive capture) or positioned outside the device (exteroceptive
capture).
This subfunction s
...