In today's world,
people interact with vast amounts of data, which is why most technologies are
aimed at simplifying the acquisition and perception of information. One such
technology is "augmented reality," which has been the subject of
extensive research since 1967. The term "Augmented Reality" was first
introduced in 1990 by T. Caudell, a researcher at Boeing, who defined it as
follows: "Augmented reality is a technology that allows graphical
information to be displayed directly onto the human retina using various
technical devices."
The authors of
this article consider augmented reality systems (ARS) as a specific case of
spatial modeling and visualization systems. Spatial modeling is used in the
creation and editing of spatial scenes, while visualization is used for their
visual representation. It should be noted that the specificity of ARS lies in
the extensive use of various complex imaginary material and abstract objects of
spatial scenes, as well as the wide range of visualization attributes for such
scenes.
Figure 1
illustrates an example of ARS. It shows a tablet running a special mobile
application that uses image recognition technology to track a drawing on the
table and overlay a virtual spatial scene with objects onto the scene,
represented as a 3D model of the surroundings of the Eiffel Tower, which was
created in a special program (see Fig. 1).
Fig. 1 - Spatial modeling and
visualization system of a spatial scene consisting of a three-dimensional model
of an abstract object, in the form of the surroundings of the Eiffel Tower,
displayed using ARS.
On Figure 2,
an illustration of another example of ARS is shown. It can be seen that a
tablet running a special mobile application uses object recognition technology
to track a mechanical installation and then overlays a spatial scene on it. The
virtual objects in the scene include a virtual layer that shows the boundaries
of the installation, as well as virtual objects in the form of pointers and
labels for the 6 stators (see Fig. 2).
Fig. 2 - Spatial modeling and
visualization system of a spatial scene consisting of a three-dimensional model
of an abstract object, in the form of an installation shell, as well as
additional objects in the form of pointers and labels on its 6 stators, displayed
using ARS.
When it comes to the history
of Augmented Reality (AR) technology [9], the idea of overlaying data onto
real-life through technological devices was first described in the novel
"The Master Key" in 1901 by L. Frank Baum. In the novel, electronic
glasses were used as the device. In 1962, Morton Heilig invented the Sensorama,
a simulator that provided sound, visual effects, and even vibrations. However,
the birth of augmented reality is considered to be in 1968 when Ivan Sutherland
invented the "Sword of Damocles" head-mounted display, which was
positioned as a window into the virtual world. In 1974, Myron Krueger opened
the "Videoplace" laboratory in Connecticut, dedicated to artificial
reality. In 1980, Steve Mann created the EyeTap, a head-mounted display that
showed virtual information in front of the user's eyes. This device is
considered the first functional model of an augmented reality headset. In 1993,
the first experimental implementations of AR in real cars and pilot simulators
by Loral WDL took place. In 1998, the first implementations on television
occurred when Sportvision displayed the yellow line during an NFL game. In
2000, Hirokazu Kato created the ARToolKit [20], a software library that is
still used today and has open-source code. In the same year, the first AR game
called AR Quake was developed. The first uses in print media occurred in 2009
when Esquire magazine used AR to bring their cover to life by adding a computer
layer with video. Also in 2009, ARToolkit[20] was ported to Adobe Flash
(FLARTToolKit[21]), allowing Saqoosha to bring AR to web browsers. In 2012, the
UK-based company Blippar created the first cloud-based AR application.
Volkswagen also made a significant contribution to the development and
application of augmented reality by creating the Marta application in 2013. It
provided repair instructions for specialists and was innovative. Later, it
found applications in various industries. The well-known Google Glass eyewear
was developed in 2014, and in the same year, Blippar[22] created the first game
for them. Following Google, Microsoft didn't keep us waiting and introduced
HoloLens in 2015, a mixed reality headset that surpassed Google Glass. In the
same year, the Association of Augmented and Virtual Reality was established in
Russia. The most famous augmented reality game in the world was "Pokemon
GO [17]," created in 2016, which significantly changed consumers'
skeptical attitude towards innovative technologies. In 2017, Apple announced
one of the most popular tools to date - ARKit[16], which is used to create
mobile applications with augmented reality. In the same year, the number of AR
users in the United States reached 37 million people, and some attribute this
to IKEA releasing the IKEA PLACE app, which transformed the retail industry.
ARCore[18] – the most popular tool for
Android device developers – was announced by Google in 2019, following Apple's
ARKit[16]. Most augmented reality applications are created using ARKit[16] and
ARCore[18], and this trend continues to the present day.
It is important to classify
Augmented Reality (AR), as described in the research paper "Classification
of Augmented Reality Applications" by Makolkina M.A.[1], written in 2020.
Augmented reality systems are classified based on:
1) Type of information
representation:
- Visual: Information is
presented to the user through images.
- Audio: Information is
presented in the form of sound.
- Audiovisual: Combination of
visual and audio information.
- Text and graphic systems:
Information is presented as text.
- Sensor-based: Information
is provided through vibrations.
- Holographic: Information is
presented using holographic images.
2) Degree of mobility:
- Stationary: These systems
cannot be moved without causing malfunctions.
- Mobile: These systems can
be moved without any disruptions.
3) Degree of user
interaction:
- Autonomous: The system's
task is to provide the user with the necessary information.
- Interactive: The system
actively interacts with the user, providing responses based on user actions.
4) Method of trigger
recognition (the object or situation that triggers the appearance of augmented
reality):
- Markerless Augmented
Reality: No markers or triggers are required.
- Marker-based Augmented
Reality: Requires a marker as a trigger.
- Geopositional: Requires GPS
and accelerometer signals to determine the angle of rotation relative to
vertical and azimuth.
- Image recognition: Requires
an object trigger (face, image, hands, or any other objects).
When it comes to the
application areas of augmented reality (AR), they are very extensive. For
example, Pantano[6] (2014) emphasizes the potential of augmented reality in
terms of "capturing consumers' attention and influencing their purchase
decisions." With the recent emergence of augmented reality and its
increasing accessibility, retailers have started relying on this interactive
technology to enhance the shopping experience and influence the decision-making
process of potential buyers. On one hand, interactive technologies in shopping
centers use specialized devices and software to explain, demonstrate, and
recommend products. On the other hand, mobile applications with augmented
reality features can be downloaded and installed on users' personal portable
devices, making them available anytime and anywhere, and therefore more
frequently used and helpful for users. In addition to adding informativeness,
the wow-factor that this technology brings cannot be denied. Due to its
novelty, users are more willing to use it more often compared to familiar
technologies. Nowadays, augmented reality is applied in various areas of our
lives, including education, marketing and advertising campaigns, proprietary
augmented reality products in the banking sector, and more.
According to many scientific articles
[1], optimal applications of augmented reality are in retail and the commercial
sector as a whole. Augmented reality is widely used for virtual fitting of
clothing and trying out technology and furniture in one's own interior space.
However, the applications of augmented reality technology are not limited to
these areas. In our view, one interesting and rational application of this
technology could be its integration into the data analysis process in visual
analytics. Currently, there is relatively little research in this area, but
such an application could be highly effective and will be described in detail
in the next chapter.
James Thomas, an American
scientist, formulated a set of ideas and concepts in the paradigm of visual
analytics for solving data analysis tasks using a supporting visual interactive
interface. One of the most widely practiced examples of visual analytics may be
the solution in terms of data analysis through visualization methods. The main
essence of this method is as follows: a static or dynamic graphical image is
associated with the object of consideration, which is visually analyzed. The
results of data analysis are interpreted graphically in relation to the
original data and the object of consideration (see Fig. 3).
Fig. 3 Data analysis through visualization
methods
What is visual analysis of
graphical data? It is important to note that visual analysis follows spatial
modeling of the original data. This means that the obtained graphical images
are intended to serve as a convenient and natural means of spatial
interpretation of the original data for analysts. The interpretation of the
spatial scene involves a series of spatial objects (either one or multiple)
that are mapped to the analyzed data during the so-called mapping stage. The
spatial scene is visually analyzed. Subsequently, the results are interpreted
in relation to the original data. Visualization method, as a data analysis
technique, is one of the methods used in spatial data modeling. This allows for
leveraging the vast capabilities of spatial thinking by analysts during the
analysis process. Ultimately, analysts make judgments about the analyzed scene.
As mentioned above, these judgments are interpreted by the analyst in relation
to the original data, forming a judgment model about the object of
consideration. In general, data analysis using visualization methods can be
interactive, iterative, and complex.
It is important to note that
visualization methods can be used to analyze data of various types, such as
different experimental and theoretical scientific data, which constitute the
essence of scientific visualization. Consequently, in data analysis using
visualization methods, the central focus is on the spatial scene, which is
mapped by the analyst to the analyzed original data and visually analyzed.
During the analysis, visual analysts perform several basic operations on the
spatial scene, including analyzing the spatial arrangement of data components,
analyzing the shape of spatial scene components, and analyzing their color
representation.
These operations have a
qualitative nature, and it is expedient to introduce additional spatial objects
into the spatial scene that are not directly related to the original data but
allow for an increased resolution in analyzing the original data. These
additional spatial objects, like the spatial scene itself, can be either static
or represent spatial processes. In modern computer science, the result of
introducing the spatial scene and similar auxiliary spatial objects into the
visual field, through technological devices such as smartphones, tablets, and
computers, for the purpose of analyzing the spatial scene, augmenting
information about the environment, and altering the perception of the
surrounding environment, as described in the previous chapter, is referred to
as augmented reality. It is important to note that as a result of such
introduction, not only do new additional objects appear, such as elements of
the spatial scene display interface, but the appearance of the spatial scene
itself is also altered.
With augmented reality
technology, analysts have the ability to analyze the spatial scene on
smartphones and tablets. This makes spatial scene analysis more accessible to a
larger number of analysts. This type of spatial scene display always occurs
against the backdrop of the working camera of one of the aforementioned
technological devices, through the operation of a specialized mobile
application or in a browser. It is precisely the accessibility of using this
type of display for subsequent analysis, as well as the presence of additional
objects within the spatial scene, that allows for informed recommendations on
the rational use of augmented reality in visual analytics. It is important to
understand at this stage whether augmented reality is already being used in the
areas related to scientific visualization and visual analytics or not.
In the work of Mrudang Mathur
and others (2022), models of augmented reality applicable to scientific
visualization are described. It is reported that this technology is rarely used
in scientific visualization due to the difficulty of creating it. It is also
emphasized that previously there were no accessible means for creating
augmented reality. The next chapter of this article will describe one of the
available online platforms for augmented reality projects, which makes it easy
to create such projects.
In the work of Namiot and
Romanov (2018) titled "3D Visualization of Architecture and Software
Metrics," they demonstrate how a pre-created 3D model of a "software
city" is embedded into a real scene using augmented reality technology.
This shows an example of how spatial scene analysis can be simplified for
analysts using this technology.
In the work of Vakhrushev
(2020), models of applying augmented reality for visualizing scientific
knowledge in an open library archive are described. Augmented reality enhances
the informativeness of the spatial scene in this context.
In the Russian market of
augmented reality, there is a monopolistic company among online platforms for
creating augmented reality projects - the Web-AR.Studio platform [11]. It
functions as an online constructor, where even a person without programming
experience or knowledge of 3D graphics can create their own augmented reality
project in a matter of minutes. Moreover, projects can be of any complexity and
can work both through a mobile application and through a browser, eliminating the
need for mobile apps. This online platform was created by two students of NRNU
MEPhI, and as a result, it was made available for use by master's and doctoral
students of NRNU MEPhI in disciplines such as "Scientific
Visualization" and "Visual Analytics".
During the planned sessions,
doctoral and master's students will create three-dimensional models based on
scientific data using the "3Ds MAX [13]" program. Subsequently, these
data models will be integrated into augmented reality projects using the Web-AR.Studio
platform [11]. This allows analysts to analyze them from any device, such as a
smartphone, tablet, or laptop. Additionally, by adding additional interface
icons on the online platform, the informativeness of the spatial scene for
analysts can be increased, as shown in Figure 2. The relevant work of doctoral
and master's students can be used in the Department of General Physics for
teaching students in introductory courses. The integration of such augmented
reality projects in physics labs enhances student engagement, resulting in
improved preparedness and faster comprehension of information. The engagement
of an augmented reality project is achieved through the interactivity of this
technology. The speed of information comprehension is achieved through the
additional interface and three-dimensional visualization, which is easier to
perceive than two-dimensional information. As humans perceive the world in
three dimensions, three-dimensional objects in augmented reality are also
quickly and easily understood compared to two-dimensional ones.
There is also an ongoing
scientific seminar on the topic of "Visual Analytics and the Use of
Augmented Reality Technology to Solve its Tasks." During this seminar,
participants can learn how to effectively utilize this technology to solve
"visual analytics" tasks.
Regarding the general
characteristics of the work on using augmented reality in visual analytics
tasks at NRNU MEPhI, using the online platform of AR Studio LLC, a range of
tasks related to the visualization of physical processes from student
laboratory work can be highlighted, as well as their work with physical
installations located in the general physics laboratories. NRNU MEPhI master's
and doctoral students will be able to recreate processes from methodological
printed documents for student laboratory work using augmented reality
technology. This will allow for faster perception and, as a result, better
assimilation of new information for NRNU MEPhI students. Currently, everything
is presented in a 2D format, in the form of printed documentation with images,
but it will be presented in a 3D format through AR technology created on the
online platform.
Regarding the description of
the online constructor itself, on the Web-AR.Studio platform [11], you can create
an augmented reality project in three different deployment variations (see
Figure 4): browser-based applications, mobile applications, and instant launch
applications. Browser-based applications work without the need to download a
mobile application, so the user does not need to spend personal time and
storage space on their device, such as a smartphone. However, the downside is
that the recognition algorithm in browser-based applications is considered less
stable and slower compared to the mobile application. On the other hand, the
advantage of the mobile application is its fast recognition algorithm, but the
downside is the need to download the application. As for the instant launch
application, it combines the advantages of the first two options, meaning it
does not require downloading and has a very fast recognition algorithm. It is
important to note that different types of publications have different maximum
numbers of simultaneously recognizable triggers. For example, a browser-based
project can have up to 9 simultaneously recognizable images and up to 1000
simultaneously recognizable QR codes, while a project in a mobile application
can have up to 100 simultaneously recognizable images. Additionally, you can
choose one of the recognition types, which can be QR code recognition, image
recognition, or markerless technology, as shown in the example with solenoid
magnetic fields (see Fig. 9).
Fig. 4 - Three deployment options for
projects on the Web-AR.Studio platform [11]
If you have any questions
about creating a project, you can ask the technical support team by clicking on
the "Help" button or refer to the platform's documentation by
clicking on the "Training" button.
Opening an augmented reality
project is done through a QR code generated based on the project's URL. On the
platform, in the top left corner of the project's main page, you can download
it in various formats such as JPG, SVG, PNG, or PDF. If marker-based augmented
reality technology is used, you can download the combined QR code and project
trigger. A trigger is an object that triggers the appearance of augmented
reality. For example, if image recognition is used, the video stream obtained
from the device's camera will be divided into frames, each frame will be
processed and compared with the uploaded image on the platform. If a match is
found, virtual augmented reality objects created by the user on the online
constructor will appear at the location of the recognized image.
When using the
"Web-AR.Studio[11]" constructor, there are also several auxiliary
functions to enhance the user's interaction with the project. These include:
1) Project personalization, which allows
you to choose the project's language, domain name, loading screen, and logo.
2) Custom analytics system, which collects
data on user interaction and experience.
3) The ability to disable the project
trigger through the default scene fixation button, to switch the project type
to markerless. This button is shown in the top part of Fig. 7. Additionally,
you can integrate well-known analytics systems such as
"Yandex.Metrica[15]" and "Google Analytics[16]".
In the editor itself, you can
choose from pre-designed project templates and modify the data to fit your
needs, or create your own project from scratch. There are two types of editors
available: a 2D editor for beginners and a 3D editor for advanced users (see
Fig. 5).
Fig. 5 - 3D editor of the Web-AR.Studio
platform [11]
In the editor itself, when
creating a project, you can upload the project trigger in the top right corner
or, if there are multiple triggers, apply batch uploading, which allows you to
apply up to 100 images as triggers at once.
Through the toolbar located
in the top left corner, you can upload various types of augmented reality
objects, including audio, text, images, videos, videos with alpha channel,
static 3D models, animated 3D models, and built-in geometric objects.
For example, in the work
"Cyber-Physical Museum Exhibits Based on Additive Technologies, Tangible
Interfaces and Scientific Visualization" (2019) by K. V. Ryabinina [24]
and others, a 3D model of a "Bonobo" skull is described and
visualized, created by scanning a real skull with a 3D scanner. It can be
integrated into this platform as a 3D model for subsequent viewing in augmented
reality.
Each augmented reality object
can have its own functions that will be triggered when the element is clicked.
Additionally, objects can have animations. In this platform, you can modify the
design of objects, their position in space, transparency, color, layer
position, and in the 3D editor, you can modify the texture and relief of the 3D
model.
Furthermore, you can even set
up lighting within the project, similar to how it is done in 3D modeling
programs like Blender [12] and "3Ds Max[13]". You can choose from
different types of lighting, such as spherical, directional, point, spotlight,
and ambient lighting (see Fig. 6).
Fig. 6 - Toolbar on the Web-AR.Studio
platform [11] with the option to select the type of lighting.
As seen in Figure 6, each scene
is divided into layers consisting of augmented reality objects. There can be
multiple scenes, and depending on whether the same triggers have different
scenes or not, projects can be created for different purposes. If a project
contains a large number of triggers, and each trigger has its own virtual
scene, it is called a multi-trigger project. For example, a brochure, album, or
book with augmented reality, where each page is recognized individually and
triggers the appearance of different augmented reality objects on the device.
When a user finishes creating
an augmented reality project and wants to preview the result, they need to
click on the "Preview" button located in the top right corner. This
will bring up a preview window with a QR code and trigger (see Fig. 7).
Fig. 7 - Preview on the Web-AR.Studio
platform [11]
This constructor allows you
to create augmented reality projects where you can use your own pre-made 3D
models and add additional objects to create a spatial scene that provides additional
information. For example, in Figure 8, an animated 3D model of a heart is
shown, with the ability to click on the screen on one of the virtual objects
located next to different parts of the heart and read about the functions of
that specific part.
Fig. 8 - Augmented reality project
created on the Web-AR.Studio platform [11] featuring an animated 3D model of a
heart and additional text information.
This is what has been done so
far, but the platform continues to evolve. In the near future, the platform
will add surface recognition algorithms and geographic augmented reality, where
augmented reality objects appear at specified latitude and longitude coordinates.
Additionally, a simplified editor will be added for instant creation of AR
projects.
Let's solve the task of
analyzing the magnetic field of a physical object using visualization with
augmented reality technology, based on the online platform Web-AR.Studio [11].
Problem statement for
scientific data analysis:
We have a subject of study -
the phenomenon of magnetic field in solenoids. We have the initial data - the
presence of two magnetic fields, namely the internal and external fields around
the solenoid. We need to obtain analytical judgments about the subject of
study, specifically the principles of operation of these magnetic fields in the
solenoid, i.e., the directions of action of these magnetic fields. The chosen
method to solve this problem in the given context is visualization using
augmented reality technology.
After setting the initial
data about the magnetic field of the solenoid, we can skip the data filtering
stage as it is not required, and proceed directly to the mapping stage. At this
stage, three-dimensional geometric objects with corresponding graphical
attributes, i.e., the main objects, are assigned to the initial data. The basic
functionality of the 3D modeling program "Blender [12]" was used at
this stage, where the virtual scene with corresponding three-dimensional
geometric objects was created based on typical images of similar processes
found in physics textbooks. The next stage is rendering, where we obtain a
graphical representation of the mapping results in augmented reality. For this,
the three-dimensional models obtained in the previous stage are integrated into
augmented reality using the software "Web-AR.Studio [11]". Additional
objects are also added to the main objects, and their characteristics are
described below the illustration. The process description was taken from the
documentation for laboratory work on interacting with solenoids. The
three-dimensional model was created using the software "Blender
[12]". Text and images were added in the toolbar located in the top left
corner of the 2D editor of the Web-AR.Studio platform [11] (see Fig. 9).
Fig. 9 - Toolbar on the Web-AR.Studio
platform [11] with the option to add text, images, and 3D models.
As a result, the resulting
scene will be presented as a three-dimensional model with additional objects
displayed on the screens of technological devices (such as smartphones,
laptops, tablets, etc.), against the backdrop of a working camera (see Fig.
10).
Fig. 10 - Resulting spatial scene in
augmented reality, consisting of a main object and additional objects.
The spatial scene represents
augmented reality against the backdrop of a working camera on a technological
device, and includes the following objects:
- Main object - an animated 3D model of
the process (see Fig. 11 (a)),
-Additional object - auxiliary image
with the process name displayed at the top (see Fig. 11 (b)),
-Additional object - auxiliary image
with a text description of the process displayed at the bottom (see Fig. 11
(c)),
-Additional object - auxiliary image of
an interface for changing the rotation axes (x, y, z) of the 3D model (see
Fig.11 (d)),
-Additional object - auxiliary image of
an interface for accessing the control instructions (see Fig. 11 (e)),
-Additional object - auxiliary image of
an interface for fixing the spatial scene (see Fig. 11 (f)),
-Additional object - auxiliary image of
an interface for enabling audio narration of the displayed process (see Fig. 11
(g)),
-Additional object - auxiliary image of
an interface for sharing the project with other users (see Fig. 11 (h)),
-Additional object - auxiliary image of
an interface for returning to the main scene with the selection of the physical
process (see Fig. 11 (i)).
a)
b)
c)
d)
e)
f)
g)
h)
i)
Fig. 11 - Main (a) and additional
objects (b), (c), (d), (e), (f), (g), (h), (i) of the resulting spatial scene
in augmented reality.
This resulting spatial scene
allows for visual analysis of the initial data, specifically the phenomenon of
magnetic fields in solenoids.
In this type of project, the
resulting spatial scene, which includes the described augmented reality
objects, is displayed against the background of the camera image transmitted
from the technological device to the analyst. Here, the analyst analyzes the virtual
processes generated during the mapping stage, which are constructed in
augmented reality during the rendering stage. It is worth noting that in most
augmented reality projects, analysts can use their technological devices (such
as smartphones) to obtain additional information about a physical object by
pointing their device at it and viewing a spatial scene. However, in our
project, the virtual objects themselves are the analyzed spatial scene. This
scene is animated during the rendering stage and allows the analyst to
understand the movement of the magnetic fields (internal and external) and
simultaneously receive additional information in text or audio format. It is
worth mentioning that for ease of subsequent analysis, the internal and
external fields were differentiated by different colors during the mapping
stage. The internal magnetic field of the solenoid is represented by the color
blue, while the external magnetic field is represented by the color green. This
project was created using the online platform Web-AR.Studio [11].
During this study, it can be
concluded that according to many authors of scientific articles, the optimal
applications of augmented reality are in retail and the commercial sector in
general. However, the applications of augmented reality go beyond these areas,
and one interesting and rational application of this technology is its
integration into the data analysis process in visual analytics.
After reviewing the works of
leading authors in this field, where they describe models of applying augmented
reality to scientific visualization, it can be concluded that this technology
is rarely used in scientific visualization due to the difficulty of creating it
and the lack of accessible tools for augmented reality creation in the past.
The works also present ways to simplify the analysis of spatial scenes for
analysts using this technology, such as visualizing scientific knowledge from
an open library archive, where augmented reality enhances the informativeness of
the spatial scene. This research confirms the benefits of using augmented
reality technology for scientific visualization and visual analytics purposes.
The online platform
"Web-AR.Studio [11]," which was previously described with an example
of its use in educational purposes, is a suitable software tool for creating
projects with augmented reality technology that analysts can use for spatial
scene analysis.
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