The document discusses proposed metadata standards for mixed augmented reality (MAR) content. It outlines metadata schemas using the 5W1H (who, what, when, where, how, why) framework to describe MAR anchors, points of interest, and recognition data. Examples are given tagging virtual content overlaid on real world locations like the Eiffel Tower and a Korean palace. The proposal aims to make MAR content interoperable across platforms by enabling searching, filtering and sharing through structured metadata fields.
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The Inspire Helsinki 2019 event brought together around 170 people from 29 countries to foster discussion and new ideas on how to realise the full potential of spatial data. The three-day event featured data challenges, practical hands-on workshops and future-oriented keynote presentations. The event was summed up in a panel discussion, in which perspectives on tackling remaining challenges were brought up.
The Inspire Helsinki 2019 event brought together around 170 people from 29 countries to foster discussion and new ideas on how to realise the full potential of spatial data. The three-day event featured data challenges, practical hands-on workshops and future-oriented keynote presentations. The event was summed up in a panel discussion, in which perspectives on tackling remaining challenges were brought up.
The Inspire Helsinki 2019 event brought together around 170 people from 29 countries to foster discussion and new ideas on how to realise the full potential of spatial data. The three-day event featured data challenges, practical hands-on workshops and future-oriented keynote presentations. The event was summed up in a panel discussion, in which perspectives on tackling remaining challenges were brought up.
Serving earth observation data with GeoServer: addressing real world requirem...GeoSolutions
Information on the latest developments in GeoServer for the support for Earth Observation data with support for the various OGC services and OpenSearch.
This presentation will dive into a development team’s use case for choosing MongoDB as their spatially enabled NoSQL solution. The talk will also cover how the integration of GeoServer can expand the accessibility of your data. GeoServer is the open source implementation of Open Geospatial Consortium (OGC) standards and a core component of the Geospatial Web.
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The Inspire Helsinki 2019 event brought together around 170 people from 29 countries to foster discussion and new ideas on how to realise the full potential of spatial data. The three-day event featured data challenges, practical hands-on workshops and future-oriented keynote presentations. The event was summed up in a panel discussion, in which perspectives on tackling remaining challenges were brought up.
The Inspire Helsinki 2019 event brought together around 170 people from 29 countries to foster discussion and new ideas on how to realise the full potential of spatial data. The three-day event featured data challenges, practical hands-on workshops and future-oriented keynote presentations. The event was summed up in a panel discussion, in which perspectives on tackling remaining challenges were brought up.
The Inspire Helsinki 2019 event brought together around 170 people from 29 countries to foster discussion and new ideas on how to realise the full potential of spatial data. The three-day event featured data challenges, practical hands-on workshops and future-oriented keynote presentations. The event was summed up in a panel discussion, in which perspectives on tackling remaining challenges were brought up.
Serving earth observation data with GeoServer: addressing real world requirem...GeoSolutions
Information on the latest developments in GeoServer for the support for Earth Observation data with support for the various OGC services and OpenSearch.
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In addition, it covers the supplementary FIWARE technologies used to implement the rest of functions typically required when architecting a complete smart solution: Identity and Access Management (IAM) functions to secure access to digital twin data, and functions enabling the interface with IoT and 3rd systems, or the connection with different tools for processing and monitoring current and historic big data.
Extending this core part, the training camp also cover how you can easily integrate FIWARE systems with blockchain networks to create audit-proof logs of processes and ensure transparency.
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In addition, it covers the supplementary FIWARE technologies used to implement the common functions typically required when architecting a complete smart solution: Identity and Access Management (IAM) functions to secure access to digital twin data and functions enabling the interface with IoT and 3rd systems, or the connection with different tools for processing and monitoring current and historical big data.
This 12-hour online training course can be used to obtain a good understanding of FIWARE and NGSI Interfaces and form the basis of studying for the FIWARE expert certification.
Extending this core part, the virtual training camp adds introductory and deep-dive sessions on how FIWARE and iSHARE technologies, brought together under the umbrella of the i4Trust initiative, can be combined to provide the means for the creation of data spaces in which multiple organizations can exchange digital twin data in a trusted and efficient manner, collaborating in the creation of innovative services based on data sharing. In addition, SMEs and Digital Innovation Hubs (DIHs) that go through this complete training and are located in countries eligible under Horizon 2020 will be equipped with the necessary know-how to apply to the recently launched i4Trust Open Call.
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Communicating with space and analysing satellite data
Azure reached beyond the clouds and bring space-born satellite data to your subscription for analysis and discovering insights.
Satellite as a service, Azure Orbital and a whole new ecosystem signal the ambition to push the limits and explore new opportunities.
In this session we are talking about geospatial AI-based analysis and a comprehensive flow that will allow you touch a vector of increasing importance for extending the cloud and helping businesses make tactical decisions.
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Satellite as a service, Azure Orbital and a whole new ecosystem signal the ambition to push the limits and explore new opportunities.
In this session we are talking about geospatial AI-based analysis and a comprehensive flow that will allow you touch a vector of increasing importance for extending the cloud and helping businesses make tactical decisions.
Azure Orbital - a fully managed cloud-based ground station as a service that enables you to communicate with your spacecrafts or satellites and generate products for customers.
AZ orbital handles machine-machine communication for the user based on the schedule and TLE location of satellites.
Azure software modules decrypt satellite data and prepare for usage.
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This training camp teaches you how FIWARE technologies and iSHARE, brought together under the umbrella of the i4Trust initiative, can be combined to provide the means for creation of data spaces in which multiple organizations can exchange digital twin data in a trusted and efficient manner, collaborating in the development of innovative services based on data sharing and creating value out of the data they share. SMEs and Digital Innovation Hubs (DIHs) will be equipped with the necessary know-how to use the i4Trust framework for creating data spaces!
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An online training course run by the FIWARE Foundation in conjunction with the i4Trust project and IShare Foundation. The core part of this virtual training camp (27 Jun - 01 Jul 2022) covered all the necessary skills to develop smart solutions powered by FIWARE. It introduces the basis of Digital Twin programming using NGSI-LD (the simple yet powerful open standard API enabling to publish and access digital twin data) combined with common smart data models
In addition, it covers the supplementary FIWARE technologies used to implement the rest of functions typically required when architecting a complete smart solution: Identity and Access Management (IAM) functions to secure access to digital twin data, and functions enabling the interface with IoT and 3rd systems, or the connection with different tools for processing and monitoring current and historic big data.
Extending this core part, the training camp also cover how you can easily integrate FIWARE systems with blockchain networks to create audit-proof logs of processes and ensure transparency.
An online training course run by the FIWARE Foundation in conjunction with the i4Trust project. The core part of this virtual training camp (21-24 June 2021) covered all the necessary skills to develop smart solutions powered by FIWARE. It introduces the basis of Digital Twin programming using linked data concepts - JSON-LD and NGSI-LD and combines these with common smart data models for the sharing and augmentation of context data.
In addition, it covers the supplementary FIWARE technologies used to implement the common functions typically required when architecting a complete smart solution: Identity and Access Management (IAM) functions to secure access to digital twin data and functions enabling the interface with IoT and 3rd systems, or the connection with different tools for processing and monitoring current and historical big data.
This 12-hour online training course can be used to obtain a good understanding of FIWARE and NGSI Interfaces and form the basis of studying for the FIWARE expert certification.
Extending this core part, the virtual training camp adds introductory and deep-dive sessions on how FIWARE and iSHARE technologies, brought together under the umbrella of the i4Trust initiative, can be combined to provide the means for the creation of data spaces in which multiple organizations can exchange digital twin data in a trusted and efficient manner, collaborating in the creation of innovative services based on data sharing. In addition, SMEs and Digital Innovation Hubs (DIHs) that go through this complete training and are located in countries eligible under Horizon 2020 will be equipped with the necessary know-how to apply to the recently launched i4Trust Open Call.
AR and Big Data: Interoperable Data Repositories for Collaborative Work Envir...AugmentedWorldExpo
Jim Novack (Talent Swarm)
Anand Gupta (Bigdatastrategy)
Collaborative Work Environments (CWE) combined with Telepresence and Mixed Reality technologies offer new ways to improve the outcomes of engineering and building large construction, petrochemical, industrial, aeronautical and defense industry projects. This presentation will describe how in the near future, design, implementation and control processes in these projects will be performed more safely and accurately at lower cost by proposing a framework of existing, open and already adopted standards.
Augmented World Expo (AWE) is back for its seventh year in our largest conference and expo featuring technologies giving us superpowers: augmented reality (AR), virtual reality (VR) and wearable tech. Join over 4,000 attendees from all over the world including a mix of CEOs, CTOs, designers, developers, creative agencies, futurists, analysts, investors, and top press in a fantastic opportunity to learn, inspire, partner, and experience first hand the most exciting industry of our times. See more at http://AugmentedWorldExpo.com
Code Camp - Building a Glass app with Wakandatroxell
A description of using the Mirror API (Google) and WakandaDB.
Source code here: https://github.com/lyle/GlassWakanda
Original Reveil Slides: http://talks-2013.lyle.troxell.com/
Presentation about the collaboration between ADAPT and the Ordnance Survey Ireland at Linked Data Seminar -- Culture, Base Registries & Visualisations held in Amsterdam, The Netherlands on the 2nd of December 2016
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Collecting and Analysing Spaceborn DataIvo Andreev
Communicating with space and analysing satellite data
Azure reached beyond the clouds and bring space-born satellite data to your subscription for analysis and discovering insights.
Satellite as a service, Azure Orbital and a whole new ecosystem signal the ambition to push the limits and explore new opportunities.
In this session we are talking about geospatial AI-based analysis and a comprehensive flow that will allow you touch a vector of increasing importance for extending the cloud and helping businesses make tactical decisions.
Collecting and Analysing Satellite Data with Azure OrbitalIvo Andreev
Azure reached beyond the clouds and bring space-born satellite data to your subscription for analysis and discovering insights.
Satellite as a service, Azure Orbital and a whole new ecosystem signal the ambition to push the limits and explore new opportunities.
In this session we are talking about geospatial AI-based analysis and a comprehensive flow that will allow you touch a vector of increasing importance for extending the cloud and helping businesses make tactical decisions.
Azure Orbital - a fully managed cloud-based ground station as a service that enables you to communicate with your spacecrafts or satellites and generate products for customers.
AZ orbital handles machine-machine communication for the user based on the schedule and TLE location of satellites.
Azure software modules decrypt satellite data and prepare for usage.
Social Media Copyright Management using Semantic Web and BlockchainRoberto García
Solutions based on distributed ledgers require sophisticated tools for data modelling and integration that can be overcome using semantic and Linked Data technologies. One example is copyright management, where we attempt to adapt the Copyright Ontology so it can be used to build applications that benefit from both worlds, rich information modelling and reasoning together with immutable and accountable information storage that provides trust and confidence on the modelled rights statements. This approach has been applied in the context of an application for the management of social media re-use for journalistic purposes.
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The relationship between the metaverse and the universe corresponds to the one between the virtual environment and the real environment in MAR (Mixed and Augmented reality). The concept of fusing multiple metaverses with the universe is sometimes referred to as the interverse, although this is not yet generally recognized. This presentation will provide an overview of the standards related to interverse developed by SC 24/WG9 (MAR Continuum Concepts and Reference Model) and the ongoing projects. In addition, VRM, an open 3D humanoid avatar format for the metaverse, will be presented, although it is not yet a de jure standard.
ISO/IEC Workshop on Standards for the Metaverse
Session 1: ISO/IEC JTC 1 Standards and Projects for the Metaverse, June 26, 2023, at 21:00-22:50 UTC
Similar to Metadata representation for outdoor AR services (20)
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Metadata representation for outdoor AR services
1. Woontack Woo, Ph.D.
KAIST UVR Lab.
Daejeon, Korea
ISO SC24 WG9, [Jan. 14, 2016]
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 1
2. Based on Two Domestic Standards
◦ TTAK.KO-10.0434 (Dec. 2010): Representation for AR: POI, Content, Link
◦ TTAK.KO-10.0851 (Dec. 2015): Metadata for AR content visualization & sharing
Proposal on “Metadata: data about data”
◦ Metadata modeling for context-aware MAR services,
what::Status, (physical/virtual object ID)
who::Role, (author profile)
when::Time, (created, modified)
where::Location, (geographical/relative position)
how::Action, (link/interaction/response method)
why::Goal,
◦ Meta-tagging: the process of adding metadata with 5W1H
to various physical/virtual assets/entities
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 2
3. Milgram's Reality-Virtuality Continuum [94]
Azuma's definition on AR [97]
◦ combines real and virtual
◦ is interactive in real time
◦ is registered in real 3D world
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 3
4. UVR: MAR for DigiLog Life (Woo)
◦ 3D Link between dual (real & virtual) spaces with
additional information
◦ CoI (Context-of-Interest) Augmentation, not just
sight: sound, haptics, smell, taste, etc.
◦ Bidirectional Interaction/collaboration (UX) in dual
spaces
SPACES
Private (3rd skin)
Social
General/Public
Real space
Social Networks
Seamless
Augmentation btw
dual spaces
How
to
Link
Seam
lessly? CoI
LINK
AR‐Content
Virtual space
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 4
5. Holistic Layers of Spaces
.
.
.
.
.
.
Real/Physical
Virtual/Cyber
Information/
Knowledge
SPACE
TIME
Layers Social/wisidom
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 5
6. MAR as Metaverse
Modeling
Interaction
Networking
SensingMetaverse
Measured
Space
Physical
Space
Virtual
Space
SensingModeling
Anchoring
(Augmentation)
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 6
9. Increased Interest and Demands on MAR
◦ Popularized since the advent of so-called “AR Browsers”
◦ Ubiquitous VR, Extended R, Cross R, co-existence R, etc.
However, Incompatible MAR Contents
◦ Most AR contents are not re-usable in other applications
◦ Different “processes, data structure/format, etc.”
◦ More importantly, differences in linking approach
The key of MAR services is
◦ Metadata for Anchoring between “Real” + “Virtual”
However,
◦ No Standardized “metadata” Format for MAR content
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 9
10. Support MAR Use Cases: Augmenting
◦ Location with Virtual Content (VC)
◦ Fixed/Movable Real Object (RO) with VC
◦ One’s own VC over Other User’s RO
◦ Multiple VC onto a RO from Multiple Users
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 10
11. Goal: Representation of Metadata Should
◦ Be platform independent and interoperable
◦ Enable searching, filtering, and sharing of MAR content with
structured fields 5W1H: (Who, When, Where, What, How) + Why
◦ Be concise, compact, yet flexible, extensible to use
Support various MAR use cases
Scope: Be able to refer
◦ PoI: real entity (person/object/space/location) or content
◦ VoI: MAR content (image, text, video, audio, 3D model)
◦ AR Anchor: Link between RC & VC:– contains the
instructions for MAR visualization
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 11
12. ISO/IEC CD 18039
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 13
14. 5W1H Metadata Schema
who MAR Contents.{Owner, Creator}
when
MAR Contents.{Created Time, Modified Time, Accessed Time,
Duration}, CHE Information.{Begin Time, End Time}
where CHE Information.{Location}
what
MAR Contents.{ID, Name, Type, Tag, Reference, MAR
Anchor.ID}, CHE Information.{Type, Description}, VO.{Type,
String, Data File}, Media Asset.{Type, Data File}
how CHE Information.{Condition state}
Anchor
PoI: Metadata1
3 MAR Content:
Metadata
5W1H Metadata Schema
who MAR Anchor.{Owner, Author}
when MAR Anchor.{Authored time, Modified time}
where
MAR Anchor.{PoI Coordinate, Contents Coordinate, Coordinate
Type}
what MAR Anchor.{ID, Tag, PoI.ID, MAR Contents.ID}
how MAR Anchor.{Scale, Interaction, Animation, Accessibility}
MAR Anchor:
Metadata2
Anchor
Real
Object
Virtual
Contents
Anchor
5W1H Metadata Schema
who Recognition Data.{Owner, Creator}
when Recognition Data.{Created Time, Modified Time}
where
PoI.{Location, Front Direction}, Recognition Data.{Personal
Device Location, PoI 3D Position}
what
PoI.{ID, Name, Tag, Recognition Data.ID, MAR Anchor.ID},
Recognition Data.{ID, Data Set ID, Sub‐Data Set ID, Current Sub
Data, Candidate Sub Data}
how
Recognition Data.{Scale, Gyroscope, Compass, Intrinsic
Parameter}
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 15
16. Meta-tagging
WHO WHEN WHERE WHAT HOW
+Virtual
Bird.{Owner,
Creator}
+Virtual
Eiffel_Tower.
{Owner,
Creator}
+Virtual Bird.{Created Time,
Modified Time, Accessed Time,
Duration}
+Virtual Eiffel_Tower.{Created
Time, Modified Time, Accessed
Time, Duration}
+Virtual Eiffel_Tower
Info.{Begin Time, End Time}
+Virtual
Eiffel_Tower
Info.{Location}
+Virtual Bird.{ID, Name,
Type, Tag, Reference,
Eiffel_Tower Anchor.ID}
+Virtual Eiffel_Tower
Info.{Type, Description}
+Virtual Eiffel_Tower
VO.{Type, String, Data
File}
+Virtual
Eiffel_Tower
Info.{Condition
state}
WHO WHEN WHERE WHAT HOW
+Eiffel_Tower
Anchor.{Own
er, Author}
+Eiffel_Tower
Anchor.{Authored
time, Modified
Time}
+Eiffel_Tower
Anchor.{PoI Coord.,
Contents Coord., Coord.
Type}
+Eiffel_Tower
Anchor.{ID, Tag,
PoI.ID, MAR
Contents.ID}
+Eiffel_Tower
Anchor.{Scale,
Interaction, Animation,
Accessibility}
2
1
3
WHO WHEN WHERE WHAT HOW
+Eiffel_Tower
Recognition.{
Owner, Creator}
+Eiffel_Tower
Recognition.{
Created Time,
Modified Time}
+Eiffel_Tower PoI.{Location,
Front Direction}
+Eiffel_Tower
Recognition.{Personal Device
Location, PoI 3D Position}
+Eiffel_Tower PoI.{ID,
Name, Tag, Rec. Data,
MAR Anchor.ID}
+Eiffel_Tower
Recognition.{ID, Data Set
ID, Candidate Sub Data}
+Eiffel_Tower
Recognition.{S
cale, Gyroscope,
Compass,
Intrinsic
Parameter}
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 17
http:.//Geovid.org
17. Korean Palace Augmentation
MAR Content
PoI
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 18
http:.//Geovid.org
18. Meta-tagging
2
1
3
WHO WHEN WHERE WHAT HOW
+Virtual
Palace.{Own
er, Creator}
+Virtual Palace.{Created Time,
Modified Time, Accessed Time,
Duration}
+Virtual Palace Info.{Begin
Time, End Time}
+Virtual
Palace
Information.{L
ocation}
+Virtual Palace
Information.{Type,
Description}
+Virtual Palace VO.{Type,
String, Data File}
+Virtual
Palace
Info.{Condi
tion state}
WHO WHEN WHERE WHAT HOW
+Palace
Anchor.{Ow
ner, Author}
+Palace
Anchor.{Authored
time, Modified Time}
+Palace Anchor.{PoI
Coord., Contents
Coord., Coord. Type}
+Palace Anchor.{ID,
Tag, PoI.ID, MAR
Contents.ID}
+Palace Anchor.{Scale,
Interaction, Animation,
Accessibility}
WHO WHEN WHERE WHAT HOW
+Palace
Recognition.
{Owner,
Creator}
+Palace
Recognition.{Create
d Time, Modified
Time}
+Palace PoI.{Location,
Front Direction}
+Palace
Recognition.{Personal
Device Location, PoI 3D
Position}
+Palace PoI.{ID, Name,
Tag, Rec. Data, MAR
Anchor.ID}
+Palace Recognition.{ID,
Data Set ID, Candidate Sub
Data}
+Palace
Recognition.{Sc
ale, Gyroscope,
Compass,
Intrinsic
Parameter}
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 19
http:.//Geovid.org
19. Metadata Structure MAR Contents Sharing
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 20
20. Now, do you think …
◦ It is useful?
◦ It is worthy of standard?
◦ Which parts?
Possible MAR Services in
◦ Tour guide services in Cultural Heritage
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 21
21. Metadata Type Definition
.ID
String or
Number
Identification of PoI instance
.Name String Name of PoI
.Tag String[] Information marking for the content searching
.Recognition
Data.ID
String or
Number
ID of Recognition Data instance called in PoI Class
.MAR Anchor
.ID
String or
Number[]
ID of MAR Anchor instance called in PoI Class
• Contains metadata fo
r the PoI
• Inherit Class:: Recogni
tion Data
• Legend
• Who
• When
• Where
• What
• How
• Call other class
• ID: CD_Palace_001
• Name: Injung-Jun
• Tag : {Palace, King, … }
MAR Anchor.ID:
{Injung_Txt, Injung_Img}
Recognition Data.ID:
Recog_Injung
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 22
22. Metadata Type Definition
.Location GPS GPS coordinate of PoI.
.Front Direction
Float (-1 or
[0,360])
Direction of front of the PoI measured by
Compass. If the PoI is view-point
invariant(i.e. symmetric) then the value is -
1(NULL)
• Contains metadata fo
r the PoI
• Inherit Class:: Recogni
tion Data
• Legend
• Who
• When
• Where
• What
• How
• Call other class
• Location : (126.9910827,37.5794506,0)
• Front Direction : 180 (Due South)
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 23
23. Metadata Type Definition
.Personal Device Locat
ion
GPS GPS coordinate of personal device
.Compass Float
User view direction on Digital Compass in
Personal Device
.Scale
Float (x, y,
z)
Real Scale of the PoI
• Point, Target image a
nd any type of data fo
r PoI recognition
• Legend
• Who
• When
• Where
• What
• How • Scale : (16.43, 10.21, 5.67) (meter)
• Compass : 76.325 (degree, North is 0)
• Personal Device Location :
(126.9910827, 37.5794506, 0.125)
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 24
24. Metadata Type Definition
.PoI 3D Position
Float (x, y,
z)
3D position of the PoI in vision-based
Local Coordinate captured by personal
device. (Center of Local Coordinate is GPS
location of PoI)
• Point, Target image a
nd any type of data fo
r PoI recognition
• Legend
• Who
• When
• Where
• What
• How
• Location : (126.9910827,37.5794506,0)
• Front Direction : 180 (Due South)
Local
Coordinate
xy
z
• PoI 3D Position:
(47.64, 12.53, 69.64)
• Location of PoI (126.9910827,37.5794506,0) become (0,0,0)
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 25
25. Metadata Type Definition
.Gyroscope
Float (x, y,
z)
3-Dim value of Camera Pose measured by
Gyroscope
.Intrinsic Parameter
Float (fx,fy
,cx,cy,k1,k
2,k3,r)
Intrinsic parameter of the embedded lens. f
x, fy are focal length of the lens. cx, cy are
principal point of the lens. (c.f. Skewness of
the cell array is 0.) k1,k2,k3,r are distortion
parameters of lens acquired by camera calib
ration. Those parameters can be converted
with respect to camera model. (In this case,
Pin-hole model)
• Point, Target image a
nd any type of data fo
r PoI recognition
• Legend
• Who
• When
• Where
• What
• How
• Intrinsic Parameter :
(3200.35, 1046.24, 1047.453, 876.23,
0.076, -0.101, -0.001, -0.001)
• Gyroscope : (28.462, 129.693, 15.23)
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 26
26. Metadata Type Definition
.ID
String or
Number
Identification of Recognition Data Instance
.Owner String
Person or group that have rights or custody
on Recognition Data
.Creator String
Person or group that create the Recognition
Data
.Created Time Time The time when recognition data was created
.Modified Time Time
The time when recognition data was
modified
• Point, Target image a
nd any type of data fo
r PoI recognition
• Legend
• Who
• When
• Where
• What
• How
• ID : Recog_Injung
• Owner : Culture Authorities
• Creator : KCTM Team
• Created Time : 2015.04.03, 17:24
• Modified Time : 2015.06.07, 14:13
Recognition
Data
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 27
27. • Point, Target image a
nd any type of data f
or PoI recognition
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.Data Set ID
String or
Number
Identification of Data file set for
recognition of certain PoI
.Sub-Data
Set ID
String or
Number
Identification of partial Data file set for
recognition of certain PoI
.Current
Sub Data
Binary file Currently utilized Sub-data file
.Candidate
Sub Data
Binary file
Possible Sub-data file utilized soon
according to the movement of User
• Data Set ID : Injung
• Sub-Data Set ID : Front 02
• Current Sub Data : Injung_Front_02.bin
• Candidate Sub Data :
Injung_Front_01.bin, Injung_Front_03.bin,
Recognition
Data
Sub-Data ID:Front 01
Injung_Front_01.bin
Sub-Data ID:Front 02
Injung_Front_02.bin
Sub-Data ID:Front 03
Injung_Front_03.bin
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 28
28. • Metadata for the
MAR visualization
• Legend
• Who
• When
• Where
• What
• How
• Call other class
Metadata Type Definition
.ID
String or
Number
Identification of MAR Anchor instance
.MAR Contents.ID
String or
Number
ID of MAR Contents instance called in MA
R Anchor Class
.PoI.
ID
String or
Number
ID of PoI instance called in MAR Anchor cl
ass
.Tag String[]
Information marking for the content searchi
ng
.Accessibility
Enum={
Public,
Private,
Custom}
Class that can access to the MAR Contents
Anchor
• PoI.ID: ID: CD_Palace_001
• MAR Contents.ID:
CD_Morning_Assembly
• Accessibility: Public
• ID: InJung_Morning_Assembly
• Tag: Palace, King, Music …
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 29
29. • Metadata for the
MAR visualization
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.Owner String
Person or group that have rights or custody
on MAR visualization anchor
.Author String
Group of user that create MAR visualization
anchor
.Authored time Time
The time when MAR visualization anchor
was created
.Modified time Time
The time when MAR visualization anchor
was modified
• Owner: Culture Authorities
• Creator : KCTM Team
• Created Time : 2015.04.03, 17:24
• Modified Time : 2015.06.07, 14:13
Anchor
• PoI.ID: ID: CD_Palace_001
• MAR Contents.ID:
CD_Morning_Assembly
• Accessibility: Public
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 30
30. • Metadata for the
MAR visualization
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.PoI Coordinate
Float (x, y,
z)
3-dim Position of PoI on Local Coordinate of
MAR scene
.Contents
Coordinate
Float (x, y
(or, z))
position of MAR Contents in MAR scene
.Coordinate
Type
Enum={Fi
xed,
Relative}
Type of Coordinate. If Fixed, fixed 2-dim
position in device display is utilized.
Otherwise, 3-dim relative position
determined by the PoI position in local
coordinate (Center of PoI becomes the center
(0) of local coordinate)
• PoI Coordinate: (25.436, 46.56, 12.4)
• Coordinate Type : Fixed
• Contents Coordinate : (4.25, 2.15)
or
• Coordinate Type : Relative
• Contents Coordinate : (-21.186, 0,-0.4)
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 31
31. • Metadata for the
MAR visualization
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.Scale
Float (x, y
(or , z))
Size of the MAR contents in MAR scene.
(dimension of the scale depends on the
content)
.Interaction
Enum={
Touch,
Drag}
How MAR Contents interacts with the user
.Animation
{Motion,
Effect,
Transformati
on}
Animation Effects applied into the MAR
contents. Actual developments depends on
the platform. Multiple choice is enabled.
• Scale : (8.5, 92.5, 12.4)
• Interaction : Touch
• Animation : Null
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 32
32. • Contains the
metadata for MAR
Contents, include
• CHE(Cultural
Heritage Entity)
Information
• VO(Virtual
Object)
• Media asset
• MAR contents is subdivided into
cultural heritage entity(CHE)
information, virtual object, and
media asset
◦ CHE information covers the text-based
cultural heritage knowledge such as
museum document
◦ Virtual object handles 2D or 3D virtual
model augmented for PoI
◦ Media asset class contains the
multimedia data related with PoI
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 33
33. • Contains the
metadata for MAR
Contents, include
• CHE(Cultural
Heritage Entity)
Information
• VO(Virtual
Object)
• Media asset
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.ID
String or
Number
Identification of MAR Contents instance
.Name String Name of the MAR contents instance
.Owner String
Person or group that have rights or custody
of MAR Contents
.Creator String
Person or group that perform create MAR
Contents
• MAR Contents.ID:
CD_Morning_Assembly
• Name: Morning Assembly
• Owner : Culture Authorities
• Creator : KCTM Team
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 34
34. • Contains the
metadata for MAR
Contents, include
• CHE(Cultural
Heritage Entity)
Information
• VO(Virtual
Object)
• Media asset
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.Created Time Time The time when MAR Contents was created
.Modified Time Time The time when MAR Contents was modified
.Accessed Time Time The last time when MAR Contents was accessed
.Duration Time Estimated time for the MAR Contents
• Created Time :
2015.04.03, 17:24
• Modified Time :
2015.06.07, 14:13
• Accessed Time :
2015.07.03, 10:48
• Duration : 38 (sec)
• MAR Contents.ID:
CD_Morning_Assembly
• Name: Morning Assembly
• Owner : Culture Authorities
• Creator : KCTM Team
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 35
35. • Contains the
metadata for MAR
Contents, include
• CHE(Cultural
Heritage Entity)
Information
• VO(Virtual
Object)
• Media asset
• Legend
• Who
• When
• Where
• What
• How
• Call other class
Metadata Type Definition
.Type
Enum={CHE,
VO, MA}
Type of the MAR contents. Can be chosen
among Cultural heritage Entity(CHE),
Virtual Object(VO), Media Asset(MA)
.Reference String[]
References of MAR Contents. Include the
all references of CHE information, Media
Asset class
.Tag String[]
Information marking for the content
searching
.MAR Anchor.ID
(String or
Number)[]
IDs of MAR Anchor instances called in
MAR Contents class
• Type : MA (Media Asset)
• Reference : CultureContents.com
• Tag : Palace, King, …
• MAR Anchor.ID:
InJung_Morning_Assembly
Anchor
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 36
36. • Information about
CHE including PoI t
hat are virtually au
gmented
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.Type
{Actor, Place, T
hing, Event, Tim
e}
Type of depicted cultural heritage entity. M
ultiple choice is enabled
.Description String
Piece of writing gives the details about the
cultural heritage entity in MAR Contents
.Location String
Name of place or address that cultural herit
age entity is located in over the certain time
-span
• Type: Event
• Description: Morning assembly
was…
• Location: Seoul-si, Jung-gu, …
Text Information
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 37
37. • Information about
CHE including PoI t
hat are virtually au
gmented
• Legend
• Who
• When
• Where
• What
• How
Metadata Type Definition
.Begin Time Time The time when PoI was brought into existence
.End Time Time
The time when PoI was took out of existence (for ins
tant event, Begin Time==End Time)
.Condition
state
String
the states of PoI characterized over the certain time-s
pan
• Begin Time: 1528-02-15
• End Time: 1528-02-15
• Condition State: Perished
Text Information
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 38
40. “The future is already here. It is just not
uniformly distributed” by William Gibson (SF
writer)
More Information
Woontack Woo, Ph.D.
Twitter: @wwoo_ct
Mail: wwoo@kaist.ac.kr
Web: http://uvr.kaist.ac.kr
ISO/IEC JTC1 SC24 Meeting (London, UK), Aug. 24-28, 2015
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 41
41. Modified MAR reference model describes the
universal workflow for any MAR service
◦ Enhanced model of the MAR reference model, which is the
proposal of international standard(ISO ISO/IEC CD 18521-
3)
to provide the generic framework for the MAR system
to promotes the interoperability of individual MAR applications
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 42
42. ISO/IEC CD 18039
ISO SC24 WG9 & Web3D Meeting 2016Jan. 11~14, 2016 43
44. Input : Physical World
Output
◦ Sensor Data (To Context Analyzer)
◦ Physical World (Personal Device Display)
Sub Module
◦ Environment Sensor: Sensors in real world
and Internet of Thing(IoT) capture the
status of the Real world that related with
user’s task that possesses potential
applicability
◦ Personal Device Embedded: capture the
information of user’s status such as
location, view point, heading direction
which can be directly exploited in PoI
recognition
Environment (or
wearable) Sensors
for Real world
capturer
Internet of Thing
(IoT)
Sensors
Sensors
GPS
Compass
Gyro sensor
Personal Device
Embedded
Camera
Context analyzer Personal
Device
Display
Physical World
Sensor Data
Physical
World
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 45
45. User Profile: set of features of the
user such as experience, knowledge,
and behavior
Input : User
Output
◦ User Context : User’s information
related with MAR service that can be
extracted from the features of user,
i.e. user profile. User Context is
provided to the context analyzer for
adaptive service.
User profile
(experience,
knowledge,
behavior)
Context Analyzer
User
User
Context
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 46
46. Context analyzer : the core component that
takes charge of background process for
MAR service
Input
◦ For PoI Analyzer
Sensor Data
PoI Recognition Data : Instances of the PoI
Recognition class for recognizing candidate PoIs
◦ For Context Processor
User Context
Ongoing
◦ Recognized PoIs : Instances of PoI class that
are for PoIs recognized in PoI Analyzer
Output
◦ Contextualized PoIs : Filtered Recognized PoIs
according to user context in Context Processor
MAR execution engine
Contextualized PoIs
Context Analyzer
PoI Analyzer
User Localization
View Point Setting
PoI Analyzing
Context Processor
Context Integration
Context Inference
Context Management
Recognized
PoIs
User profile
User
Context
Sensors
Sensor
Data
Recognition
Data
PoI Recognition
Data
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 47
47. Input
◦ Contextualized PoIs : PoIs that are candidates to
visualize in MAR Execution Engine
◦ Related MAR content : Instances of MAR Content
class containing information of cultural heritage
entity, media asset and virtual object that is called by
MAR Anchor instance according to the instances of
Selected PoI
◦ User Commend: Commend to control MAR service
that is entered from the user interface on the
personal device display
Output
◦ MAR visualization: Result of the rendering and
simulation process in MAR execution Engine.
◦ Open API: Enables the service to be utilized in
external services
External
Services
Simulator
(event, space)
Renderer
MAR Execution Engine
Open API
Personal
Device
Display
Contextualized PoIs
MAR ContentsMAR
Anchor
Selected
PoI
Related
MAR Contents
Context Analyzer
MAR
Visualization
User
Command
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 48
48. Input
◦ Physical World: Background of the MAR Scene to
be augmented with MAR visualization
◦ MAR Visualization: Result of visualization process
of the PoI in MAR execution engine as response
of user’s input
◦ User input: Input of user to interact with the
MAR Scene
Output
◦ Enhanced Experience: Terminal goal of the
whole MAR reference model that is provided to
user
◦ User Commend: Instruction converted from user
input through user interface to control MAR
visualization
Personal Device Display
User
Interface
MAR Scene
(events, targets, …)
Enhanced
Experience
Sensors
Physical
World
MAR Execution
Engine
User
User
Input
User
User
Commend
MAR
Execution
Engine
MAR
Visualization
ISO SC24 WG9 & Web3D Meeting 2016 Jan. 11~14, 2016 49