SlideShare une entreprise Scribd logo
1  sur  19
Télécharger pour lire hors ligne
Slides: http://www.slideshare.net/christian.timmerer 
Quality of Experience beyond Audio- 
Visual: Sensory Experience (QuaSE) 
Christian Timmerer 
Alpen-Adria-Universität Klagenfurt (AAU)  Faculty of Technical Sciences (TEWI)  Department of Information 
Technology (ITEC)  Multimedia Communication (MMC)  Sensory Experience Lab (SELab) 
blog.timmerer.com  selab.itec.aau.at  dash.itec.aau.at 
christian.timmerer@itec.aau.at 
5th European Workshop on Visual Information Processing (EUVIP’14) 
December 10, 2014 
Acknowledgments. This work was supported in part by the European Commission in the context of the NoE INTERMEDIA (NoE 
038419), the P2P-Next project (FP7-ICT-216217), the ALICANTE project (FP7-ICT-248652), the SocialSensor project (FP7-ICT-287975), 
and the COST Action IC1003 QUALINET. 
Change log: 
- Dec’14: EUVIP’14, Paris, France 
- Oct’14: QUALINET Final Workshop, 
Delft, The Netherlands
Sensory Experience 
• Consumption of multimedia content may stimulate also 
other senses 
– Vision or hearing [incl. emotion, sensation] 
– Olfaction, mechanoreception, thermoception, … 
• Annotation with metadata providing so-called sensory 
effects that steer appropriate devices capable of 
rendering these effects 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 2
Sensory Experience 
• Consumption of multimedia content may stimulate also 
other senses 
– Vision or hearing [incl. emotion, sensation] 
– Olfaction, mechanoreception, thermoception, … 
• Annotation with metadata providing so-called sensory 
effects that steer appropriate devices capable of 
rendering these effects 
… giving her/him the sensation of being part 
of the particular mulsemedia 
➪ worthwhile, informative user experience 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 3
General Principle – Outline 
• General principle: there is a need for a 
scientific framework to capture, measure, 
quantify, judge, and explain the quality of 
(sensory) experience 
• Outline 
– [How to create, deliver, consume?] 
– How to capture and measure? 
– How to quantify? 
– How to judge and explain? 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 4
How to create, delivery, consume? 
• Sensory Effect Description Language (SEDL) 
– Basic building blocks to describe, e.g., light, wind, fog, vibration, scent 
– MPEG-V Part 3, Sensory Information: Effects, GroupOfEffects 
– Adopted MPEG-21 DIA tools for adding time information 
(synchronization) 
• Description conforming to SEDL :== Sensory Effect Metadata (SEM) 
– Can be associated to any kind of multimedia content (e.g., movies, 
music, Web sites, games) 
– Support to be included in file (MP4) and transport (M2TS) formats 
• Tool support for creating (annotation tools) and consumption 
(players, Web plugins) ➜ selab.itec.aau.at 
• Devices: e.g., amBX (Ambient Experience) system + SDK, 
Gameskunk, Scentscape, etc. 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 5
How to capture and measure? 
• Subjective quality assessments 
– Methodology: based on standard methods 
– Test content: different genres, manually annotated (cf. QUALINET DB) 
• Experiment I 
– Aim: Demonstrate sensory effects as a vital tool for enhancing the quality of 
experience depending on the actual genre 
• Experiment II 
– Aim: investigate the relationship of the QoE to various video bit-rates of 
multimedia contents annotated with sensory effects. 
– Subjective quality gap between video resources annotated with and without 
sensory effects at different bit-rates 
• [Experiment III] ambient lights & different color calculation settings 
• Experiment IV 
– Aim: investigate the enhancement of the QoE and how users’ emotions are 
elicited and influenced by Web videos annotated with and without sensory 
effects 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 6
Experiment II: Results 
Test Sequences 
Sequence Babylon A.D. Earth 
Duration 35s 21s 
Resolution 1280 x 544 1280 x 720 
Motion High Low 
Nr. of Effects W: 7; V: 9 W: 8; V: 1 
Bit-rates Kbit/s PSNR Kbit/s PSNR 
Low Quality 2154 38.93 2204 38.11 
Medium Quality 3112 41.27 3171 40.65 
High Quality 4044 42.95 4116 42.27 
Highest Quality 6315 N/A 6701 N/A 
MOS vs. PSNR/bit-rate for Earth. 
M. Waltl, C. Timmerer H. Hellwagner, "Increasing the User Experience of Multimedia Presentations with 
Sensory Effects," WIAMIS’10, Desenzano del Garda, Italy, April 2010. 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 7
How to quantify? 
• Experiment V 
– Aim: towards a quality/utility model for QuaSE 
• Stimuli with all 
combinations of 
sensory effects 
– Vibration higher impact 
than light & wind 
– Highest QoE with all 
effects present 
• General QuaSE model 
C. Timmerer, B. Rainer, M. Waltl, "A Utility Model for Sensory 
Experience," QoMEX’13, Klagenfurt, Austria, 2013. 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 8
How to judge and explain? 
• Experiment VI 
– Aim: understand QuaSE 
• Biosensor-based QoE evaluation system 
J. Donley, C. Ritz, M. Shujau, "Analysing the Quality 
of Experience of Multisensory Media from 
Measurements of Physiological Responses,” 
QoMEX’14, Singapore, Sep. 2014. 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 9
How to judge and explain? 
• Experiment VII 
– Aim: understand QuaSE 
• EEG Correlates of Pleasant and Unpleasant Odor 
Perception 
E. Kroupi, A. Yazdani, J.-M. Vesin, T. Ebrahimi, "EEG Correlates of Pleasant and Unpleasant Odor 
Perception," ACM TOMM, vol. 11, no. 1s, Sep. 2014. 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 10
How to judge and explain? 
• Experiment VIII 
– Aim: understand QuaSE 
• Multiple-Scent Enhanced Multimedia Synchronization 
General temporal boundaries: 
-10s to +15s are “in-sync”, 
skew values beyond are “out-of-sync” 
N. Murray, B. Lee, Y. Qiao, and G.-M. Muntean, "Multiple-Scent Enhanced Multimedia Synchronization," 
ACM TOMM, vol. 11, no. 1s, Sep. 2014. 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 11
Conclusions 
• From the need for a scientific framework to 
capture, measure, quantify, judge, and 
explain the quality of experience 
• To … 
– How to create, deliver, consume? 
– How to capture and measure? 
– How to quantify? 
– How to judge and explain? 
• Open issues? 
✔︎ 
✔︎ 
✔︎ 
✔︎ 
Still Many! 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 12
Open Issues / Challenges 
• QoE assessment is a delicate mixture of ingredients and 
choices 
– Test & lab environment 
– Test content 
– Test methodology 
– Data analysis 
• (Semi-)Automatic content creation/annotation 
• Towards large scale deployment 
– Lessons learnt from 3D (disaster) 
– 4D, 5D, xD – adding another dimension does not guarantee 
success 
• Holistic approach not feasible 
– Need for much more specialized QuaSE models 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 13
Assessing Quality of Experience … A Bit 
Like Measuring ‘Happiness’ … 
© F. Pereira, Instituto Superior Técnico, Univ. Lisboa, Portugal 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 14
Sensory Experience Lab 
http://selab.itec.aau.at/ 
Software and Services 
Standardization 
Publications 
Media 
Funding 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 15
References 
• Markus Waltl, Christian Timmerer, Hermann Hellwagner, “A Test-Bed for Quality of Multimedia Experience Evaluation of 
Sensory Effects”, Proceedings of the First International Workshop on Quality of Multimedia Experience (QoMEX 2009), San 
Diego, USA, July 29-31, 2009. 
• C. Timmerer, J. Gelissen, M. Waltl, H. Hellwagner, “Interfacing with Virtual Worlds”, Proceedings of the NEM Summit 2009, 
Saint-Malo, France, September 28-30, 2009. 
• M. Waltl, C. Timmerer H. Hellwagner, “Increasing the User Experience of Multimedia Presentations with Sensory Effects”, 
Proceedings of the 11th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS’10), 
Desenzano del Garda, Italy, April 12-14, 2010. 
• M. Waltl, C. Timmerer, H. Hellwagner, “Improving the Quality of Multimedia Experience through Sensory Effects”, 
Proceedings of the 2nd International Workshop on Quality of Multimedia Experience (QoMEX2010), Trondheim, Norway, 
June 21-23, 2010. 
• C. Timmerer, M. Waltl, B. Rainer, H. Hellwagner, “Assessing the Quality of Sensory Experience for Multimedia 
Presentations”, Signal Processing: Image Communication, 2012. 
• M. Waltl, C. Timmerer, B. Rainer, H. Hellwagner, ”Sensory Effects for Ambient Experiences in the World Wide Web”, 
Multimedia Tools and Applications (MTAP), 2012. 
• B. Rainer, M. Waltl, Eva Cheng, Muawiyath Shujau, C. Timmerer, Stephen Davis, Ian Burnett, Christian Ritz, H. Hellwagner, 
”Investigating the Impact of Sensory Effects on the Quality of Experience and Emotional Response in Web Videos”, 
Proceedings of 4th Int’l. Workshop on Quality of Multimedia Experience (QoMEX2012), 2012. 
• M. Waltl, C. Timmerer, B. Rainer, H. Hellwagner, “Sensory Effect Dataset and Test Setups”, Proceedings of 4th Int’l. 
Workshop on Quality of Multimedia Experience (QoMEX2012), 2012. 
• C. Timmerer, B. Rainer, M. Waltl, “A Utility Model for Sensory Experience”, In Proceedings of the 5th International 
Workshop on Quality of Multimedia Experience (QoMEX2013), 2013. 
• J. Donley, C. Ritz, M. Shujau, “Analysing the Quality of Experience of Multisensory Media from Measurements of 
Physiological Responses,” In Proceedings of the 5th International Workshop on Quality of Multimedia Experience 
(QoMEX2014), Singapore, 2014. 
• E. Kroupi, A. Yazdani, J.-M. Vesin, T. Ebrahimi, "EEG Correlates of Pleasant and Unpleasant Odor Perception," ACM TOMM, 
vol. 11, no. 1s, Sep. 2014. 
• N. Murray, B. Lee, Y. Qiao, and G.-M. Muntean, "Multiple-Scent Enhanced Multimedia Synchronization," ACM TOMM, vol. 
11, no. 1s, Sep. 2014. 
• G. Ghinea, C. Timmerer, W. Lin, and S. R. Gulliver. "Mulsemedia: State of the Art, Perspectives, and Challenges," ACM 
TOMM, vol. 11, no. 1s, Sep. 2014. 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 16
Thank you for your attention 
... questions, comments, etc. are welcome … 
Assoc-Prof. Dipl.-Ing. Dr. Christian Timmerer 
Klagenfurt University, Department of Information Technology (ITEC) 
Universitätsstrasse 65-67, A-9020 Klagenfurt, AUSTRIA 
christian.timmerer@itec.uni-klu.ac.at 
http://research.timmerer.com/ 
Tel: +43/463/2700 3621 Fax: +43/463/2700 3699 
© Copyright: Christian Timmerer 
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 17
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 18
2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 19

Contenu connexe

Tendances

Principles of composition
Principles of compositionPrinciples of composition
Principles of compositionBev Towns
 
What is script writing
What is script writingWhat is script writing
What is script writingVanishadoshi
 
CHAPTER – 9 Camera Shots & Angles
CHAPTER – 9    Camera Shots & AnglesCHAPTER – 9    Camera Shots & Angles
CHAPTER – 9 Camera Shots & AnglesAmir Ibrahim Tahir
 
Working with shadows
Working with shadowsWorking with shadows
Working with shadowsJessica Young
 
Film Studies. - Lesson 1 intro and camera shots
Film Studies. - Lesson 1 intro and camera shotsFilm Studies. - Lesson 1 intro and camera shots
Film Studies. - Lesson 1 intro and camera shotsElle Sullivan
 
An Introduction to Documentary Films
An Introduction to Documentary FilmsAn Introduction to Documentary Films
An Introduction to Documentary FilmsMegan Fulham
 
Adobe Premiere Pro: An Introduction to the Basics_Mujeeb Riaz
Adobe Premiere Pro: An Introduction to the Basics_Mujeeb RiazAdobe Premiere Pro: An Introduction to the Basics_Mujeeb Riaz
Adobe Premiere Pro: An Introduction to the Basics_Mujeeb RiazMujeeb Riaz
 
Plot structure powerpoint
Plot structure powerpointPlot structure powerpoint
Plot structure powerpointPaula Layton
 
Writing a film script (introduction to the basics)
Writing a film script (introduction to the basics)Writing a film script (introduction to the basics)
Writing a film script (introduction to the basics)iain bruce
 
Types of Camera and Lighting in Media
Types of Camera and Lighting in MediaTypes of Camera and Lighting in Media
Types of Camera and Lighting in Media09smisebmedia
 
Script writing for level 1
Script writing for level 1Script writing for level 1
Script writing for level 1hwells2101
 
Literary Elements
Literary ElementsLiterary Elements
Literary Elementsjtrometter
 
How do you analyse an artwork
How do you analyse an artworkHow do you analyse an artwork
How do you analyse an artworkcharlottefrost
 
History of Animation
History of AnimationHistory of Animation
History of AnimationAkhdan Hyder
 
Elements of a short story 12
Elements of a short story 12Elements of a short story 12
Elements of a short story 12jtrometter
 

Tendances (20)

Principles of composition
Principles of compositionPrinciples of composition
Principles of composition
 
What is script writing
What is script writingWhat is script writing
What is script writing
 
Example client briefs
Example client briefsExample client briefs
Example client briefs
 
CHAPTER – 9 Camera Shots & Angles
CHAPTER – 9    Camera Shots & AnglesCHAPTER – 9    Camera Shots & Angles
CHAPTER – 9 Camera Shots & Angles
 
Working with shadows
Working with shadowsWorking with shadows
Working with shadows
 
Comic Strip PowerPoint
Comic Strip PowerPointComic Strip PowerPoint
Comic Strip PowerPoint
 
Film Studies. - Lesson 1 intro and camera shots
Film Studies. - Lesson 1 intro and camera shotsFilm Studies. - Lesson 1 intro and camera shots
Film Studies. - Lesson 1 intro and camera shots
 
Introduction to drama
Introduction to dramaIntroduction to drama
Introduction to drama
 
An Introduction to Documentary Films
An Introduction to Documentary FilmsAn Introduction to Documentary Films
An Introduction to Documentary Films
 
Adobe Premiere Pro: An Introduction to the Basics_Mujeeb Riaz
Adobe Premiere Pro: An Introduction to the Basics_Mujeeb RiazAdobe Premiere Pro: An Introduction to the Basics_Mujeeb Riaz
Adobe Premiere Pro: An Introduction to the Basics_Mujeeb Riaz
 
History of animation
History of animationHistory of animation
History of animation
 
Plot structure powerpoint
Plot structure powerpointPlot structure powerpoint
Plot structure powerpoint
 
Writing a film script (introduction to the basics)
Writing a film script (introduction to the basics)Writing a film script (introduction to the basics)
Writing a film script (introduction to the basics)
 
Types of Camera and Lighting in Media
Types of Camera and Lighting in MediaTypes of Camera and Lighting in Media
Types of Camera and Lighting in Media
 
Script writing for level 1
Script writing for level 1Script writing for level 1
Script writing for level 1
 
12 principles of animation
12 principles of animation12 principles of animation
12 principles of animation
 
Literary Elements
Literary ElementsLiterary Elements
Literary Elements
 
How do you analyse an artwork
How do you analyse an artworkHow do you analyse an artwork
How do you analyse an artwork
 
History of Animation
History of AnimationHistory of Animation
History of Animation
 
Elements of a short story 12
Elements of a short story 12Elements of a short story 12
Elements of a short story 12
 

Similaire à Quality of Sensory Experience (QuaSE)

A Test-bed For Quality of Multimedia Experience Evaluation of Sensory Effects
A Test-bed For Quality of Multimedia Experience Evaluation of Sensory EffectsA Test-bed For Quality of Multimedia Experience Evaluation of Sensory Effects
A Test-bed For Quality of Multimedia Experience Evaluation of Sensory EffectsAlpen-Adria-Universität
 
Quality of Experience for Inter-Destination Media Synchronization
Quality of Experience for Inter-Destination Media SynchronizationQuality of Experience for Inter-Destination Media Synchronization
Quality of Experience for Inter-Destination Media SynchronizationAlpen-Adria-Universität
 
Immersive Future Media Technologies: Sensory Experience
Immersive Future Media Technologies: Sensory ExperienceImmersive Future Media Technologies: Sensory Experience
Immersive Future Media Technologies: Sensory ExperienceAlpen-Adria-Universität
 
The MEDEA Awards 2008: encouraging the use of video and sound in education
The MEDEA Awards 2008: encouraging the use of video and sound in educationThe MEDEA Awards 2008: encouraging the use of video and sound in education
The MEDEA Awards 2008: encouraging the use of video and sound in educationClive Young
 
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...maranlar
 
The MEDEA Awards: recognising excellence in the use of digital video and audi...
The MEDEA Awards: recognising excellence in the use of digital video and audi...The MEDEA Awards: recognising excellence in the use of digital video and audi...
The MEDEA Awards: recognising excellence in the use of digital video and audi...MEDEA Awards
 
2015-11-25 research seminar
2015-11-25 research seminar2015-11-25 research seminar
2015-11-25 research seminarifi8106tlu
 
EMuRgency: New approaches for resuscitation support and training. Overview ab...
EMuRgency: New approaches for resuscitation support and training. Overview ab...EMuRgency: New approaches for resuscitation support and training. Overview ab...
EMuRgency: New approaches for resuscitation support and training. Overview ab...Marco Kalz
 
Activity Recognition using RGBD
Activity Recognition using RGBDActivity Recognition using RGBD
Activity Recognition using RGBDnazlitemu
 
AVATAR - Added Value of teaching in a virtual world
AVATAR - Added Value of teaching in a virtual worldAVATAR - Added Value of teaching in a virtual world
AVATAR - Added Value of teaching in a virtual worldCristina Stefanelli
 
Euroversity_Slanguages2014
Euroversity_Slanguages2014Euroversity_Slanguages2014
Euroversity_Slanguages2014Ton Koenraad
 
Podcasts as a_tool_for_feedback
Podcasts as a_tool_for_feedbackPodcasts as a_tool_for_feedback
Podcasts as a_tool_for_feedbackgriesbau
 
Telecentre Multimedia Academy: project presentation
Telecentre Multimedia Academy: project presentationTelecentre Multimedia Academy: project presentation
Telecentre Multimedia Academy: project presentationTELECENTRE EUROPE
 
CAMS GA Communication activities
CAMS GA Communication activitiesCAMS GA Communication activities
CAMS GA Communication activitiesCopernicus ECMWF
 

Similaire à Quality of Sensory Experience (QuaSE) (20)

MPEG-V Part 3 enabling Sensory Experience
MPEG-V Part 3 enabling Sensory ExperienceMPEG-V Part 3 enabling Sensory Experience
MPEG-V Part 3 enabling Sensory Experience
 
A Test-bed For Quality of Multimedia Experience Evaluation of Sensory Effects
A Test-bed For Quality of Multimedia Experience Evaluation of Sensory EffectsA Test-bed For Quality of Multimedia Experience Evaluation of Sensory Effects
A Test-bed For Quality of Multimedia Experience Evaluation of Sensory Effects
 
Quality of Experience for Inter-Destination Media Synchronization
Quality of Experience for Inter-Destination Media SynchronizationQuality of Experience for Inter-Destination Media Synchronization
Quality of Experience for Inter-Destination Media Synchronization
 
Immersive Future Media Technologies: Sensory Experience
Immersive Future Media Technologies: Sensory ExperienceImmersive Future Media Technologies: Sensory Experience
Immersive Future Media Technologies: Sensory Experience
 
The MEDEA Awards 2008: encouraging the use of video and sound in education
The MEDEA Awards 2008: encouraging the use of video and sound in educationThe MEDEA Awards 2008: encouraging the use of video and sound in education
The MEDEA Awards 2008: encouraging the use of video and sound in education
 
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...
Multimedia Information Retrieval: Bytes and pixels meet the challenges of hum...
 
MPEG-V: Media Context and Control
MPEG-V: Media Context and ControlMPEG-V: Media Context and Control
MPEG-V: Media Context and Control
 
The MEDEA Awards: recognising excellence in the use of digital video and audi...
The MEDEA Awards: recognising excellence in the use of digital video and audi...The MEDEA Awards: recognising excellence in the use of digital video and audi...
The MEDEA Awards: recognising excellence in the use of digital video and audi...
 
Interfacing with Virtual Worlds
Interfacing with Virtual WorldsInterfacing with Virtual Worlds
Interfacing with Virtual Worlds
 
2015-11-25 research seminar
2015-11-25 research seminar2015-11-25 research seminar
2015-11-25 research seminar
 
EMuRgency: New approaches for resuscitation support and training. Overview ab...
EMuRgency: New approaches for resuscitation support and training. Overview ab...EMuRgency: New approaches for resuscitation support and training. Overview ab...
EMuRgency: New approaches for resuscitation support and training. Overview ab...
 
Activity Recognition using RGBD
Activity Recognition using RGBDActivity Recognition using RGBD
Activity Recognition using RGBD
 
Ict in learning
Ict in learningIct in learning
Ict in learning
 
control room design.pdf
control room design.pdfcontrol room design.pdf
control room design.pdf
 
AVATAR - Added Value of teaching in a virtual world
AVATAR - Added Value of teaching in a virtual worldAVATAR - Added Value of teaching in a virtual world
AVATAR - Added Value of teaching in a virtual world
 
Euroversity_Slanguages2014
Euroversity_Slanguages2014Euroversity_Slanguages2014
Euroversity_Slanguages2014
 
Podcasts as a_tool_for_feedback
Podcasts as a_tool_for_feedbackPodcasts as a_tool_for_feedback
Podcasts as a_tool_for_feedback
 
Telecentre Multimedia Academy: project presentation
Telecentre Multimedia Academy: project presentationTelecentre Multimedia Academy: project presentation
Telecentre Multimedia Academy: project presentation
 
CAMS GA Communication activities
CAMS GA Communication activitiesCAMS GA Communication activities
CAMS GA Communication activities
 
ZMML
ZMMLZMML
ZMML
 

Plus de Alpen-Adria-Universität

Content-adaptive Video Coding for HTTP Adaptive Streaming
Content-adaptive Video Coding for HTTP Adaptive StreamingContent-adaptive Video Coding for HTTP Adaptive Streaming
Content-adaptive Video Coding for HTTP Adaptive StreamingAlpen-Adria-Universität
 
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...Alpen-Adria-Universität
 
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...
Empowerment of Atypical Viewers  via Low-Effort Personalized Modeling  of Vid...Empowerment of Atypical Viewers  via Low-Effort Personalized Modeling  of Vid...
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...Alpen-Adria-Universität
 
Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...
Optimizing Video Streaming  for Sustainability and Quality: The Role of Prese...Optimizing Video Streaming  for Sustainability and Quality: The Role of Prese...
Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...Alpen-Adria-Universität
 
Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...
Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...
Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...Alpen-Adria-Universität
 
Machine Learning Based Resource Utilization Prediction in the Computing Conti...
Machine Learning Based Resource Utilization Prediction in the Computing Conti...Machine Learning Based Resource Utilization Prediction in the Computing Conti...
Machine Learning Based Resource Utilization Prediction in the Computing Conti...Alpen-Adria-Universität
 
Evaluation of Quality of Experience of ABR Schemes in Gaming Stream
Evaluation of Quality of Experience of ABR Schemes in Gaming StreamEvaluation of Quality of Experience of ABR Schemes in Gaming Stream
Evaluation of Quality of Experience of ABR Schemes in Gaming StreamAlpen-Adria-Universität
 
Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...
Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...
Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...Alpen-Adria-Universität
 
Multi-access Edge Computing for Adaptive Video Streaming
Multi-access Edge Computing for Adaptive Video StreamingMulti-access Edge Computing for Adaptive Video Streaming
Multi-access Edge Computing for Adaptive Video StreamingAlpen-Adria-Universität
 
Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment
Policy-Driven Dynamic HTTP Adaptive Streaming Player EnvironmentPolicy-Driven Dynamic HTTP Adaptive Streaming Player Environment
Policy-Driven Dynamic HTTP Adaptive Streaming Player EnvironmentAlpen-Adria-Universität
 
VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...
VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...
VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...Alpen-Adria-Universität
 
Energy Consumption in Video Streaming: Components, Measurements, and Strategies
Energy Consumption in Video Streaming: Components, Measurements, and StrategiesEnergy Consumption in Video Streaming: Components, Measurements, and Strategies
Energy Consumption in Video Streaming: Components, Measurements, and StrategiesAlpen-Adria-Universität
 
Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...
Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...
Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...Alpen-Adria-Universität
 
Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning
Video Coding Enhancements for HTTP Adaptive Streaming Using Machine LearningVideo Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning
Video Coding Enhancements for HTTP Adaptive Streaming Using Machine LearningAlpen-Adria-Universität
 
Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...
Optimizing  QoE and Latency of  Live Video Streaming Using  Edge Computing  a...Optimizing  QoE and Latency of  Live Video Streaming Using  Edge Computing  a...
Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...Alpen-Adria-Universität
 
SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications
SARENA: SFC-Enabled Architecture for Adaptive Video Streaming ApplicationsSARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications
SARENA: SFC-Enabled Architecture for Adaptive Video Streaming ApplicationsAlpen-Adria-Universität
 
Immersive Video Delivery: From Omnidirectional Video to Holography
Immersive Video Delivery: From Omnidirectional Video to HolographyImmersive Video Delivery: From Omnidirectional Video to Holography
Immersive Video Delivery: From Omnidirectional Video to HolographyAlpen-Adria-Universität
 
LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...
LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...
LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...Alpen-Adria-Universität
 
HTTP Adaptive Streaming – Quo Vadis? (2023)
HTTP Adaptive Streaming – Quo Vadis? (2023)HTTP Adaptive Streaming – Quo Vadis? (2023)
HTTP Adaptive Streaming – Quo Vadis? (2023)Alpen-Adria-Universität
 
How to Optimize Dynamic Adaptive Video Streaming? Challenges and Solutions
How to Optimize Dynamic Adaptive Video Streaming? Challenges and SolutionsHow to Optimize Dynamic Adaptive Video Streaming? Challenges and Solutions
How to Optimize Dynamic Adaptive Video Streaming? Challenges and SolutionsAlpen-Adria-Universität
 

Plus de Alpen-Adria-Universität (20)

Content-adaptive Video Coding for HTTP Adaptive Streaming
Content-adaptive Video Coding for HTTP Adaptive StreamingContent-adaptive Video Coding for HTTP Adaptive Streaming
Content-adaptive Video Coding for HTTP Adaptive Streaming
 
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video...
 
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...
Empowerment of Atypical Viewers  via Low-Effort Personalized Modeling  of Vid...Empowerment of Atypical Viewers  via Low-Effort Personalized Modeling  of Vid...
Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Vid...
 
Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...
Optimizing Video Streaming  for Sustainability and Quality: The Role of Prese...Optimizing Video Streaming  for Sustainability and Quality: The Role of Prese...
Optimizing Video Streaming for Sustainability and Quality: The Role of Prese...
 
Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...
Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...
Energy-Efficient Multi-Codec Bitrate-Ladder Estimation for Adaptive Video Str...
 
Machine Learning Based Resource Utilization Prediction in the Computing Conti...
Machine Learning Based Resource Utilization Prediction in the Computing Conti...Machine Learning Based Resource Utilization Prediction in the Computing Conti...
Machine Learning Based Resource Utilization Prediction in the Computing Conti...
 
Evaluation of Quality of Experience of ABR Schemes in Gaming Stream
Evaluation of Quality of Experience of ABR Schemes in Gaming StreamEvaluation of Quality of Experience of ABR Schemes in Gaming Stream
Evaluation of Quality of Experience of ABR Schemes in Gaming Stream
 
Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...
Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...
Network-Assisted Delivery of Adaptive Video Streaming Services through CDN, S...
 
Multi-access Edge Computing for Adaptive Video Streaming
Multi-access Edge Computing for Adaptive Video StreamingMulti-access Edge Computing for Adaptive Video Streaming
Multi-access Edge Computing for Adaptive Video Streaming
 
Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment
Policy-Driven Dynamic HTTP Adaptive Streaming Player EnvironmentPolicy-Driven Dynamic HTTP Adaptive Streaming Player Environment
Policy-Driven Dynamic HTTP Adaptive Streaming Player Environment
 
VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...
VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...
VE-Match: Video Encoding Matching-based Model for Cloud and Edge Computing In...
 
Energy Consumption in Video Streaming: Components, Measurements, and Strategies
Energy Consumption in Video Streaming: Components, Measurements, and StrategiesEnergy Consumption in Video Streaming: Components, Measurements, and Strategies
Energy Consumption in Video Streaming: Components, Measurements, and Strategies
 
Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...
Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...
Exploring the Energy Consumption of Video Streaming: Components, Challenges, ...
 
Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning
Video Coding Enhancements for HTTP Adaptive Streaming Using Machine LearningVideo Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning
Video Coding Enhancements for HTTP Adaptive Streaming Using Machine Learning
 
Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...
Optimizing  QoE and Latency of  Live Video Streaming Using  Edge Computing  a...Optimizing  QoE and Latency of  Live Video Streaming Using  Edge Computing  a...
Optimizing QoE and Latency of Live Video Streaming Using Edge Computing a...
 
SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications
SARENA: SFC-Enabled Architecture for Adaptive Video Streaming ApplicationsSARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications
SARENA: SFC-Enabled Architecture for Adaptive Video Streaming Applications
 
Immersive Video Delivery: From Omnidirectional Video to Holography
Immersive Video Delivery: From Omnidirectional Video to HolographyImmersive Video Delivery: From Omnidirectional Video to Holography
Immersive Video Delivery: From Omnidirectional Video to Holography
 
LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...
LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...
LLL-CAdViSE: Live Low-Latency Cloud-based Adaptive Video Streaming Evaluation...
 
HTTP Adaptive Streaming – Quo Vadis? (2023)
HTTP Adaptive Streaming – Quo Vadis? (2023)HTTP Adaptive Streaming – Quo Vadis? (2023)
HTTP Adaptive Streaming – Quo Vadis? (2023)
 
How to Optimize Dynamic Adaptive Video Streaming? Challenges and Solutions
How to Optimize Dynamic Adaptive Video Streaming? Challenges and SolutionsHow to Optimize Dynamic Adaptive Video Streaming? Challenges and Solutions
How to Optimize Dynamic Adaptive Video Streaming? Challenges and Solutions
 

Dernier

Cybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxCybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxGDSC PJATK
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024D Cloud Solutions
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1DianaGray10
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8DianaGray10
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfinfogdgmi
 
9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding TeamAdam Moalla
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesDavid Newbury
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfAijun Zhang
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Brian Pichman
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfDaniel Santiago Silva Capera
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Will Schroeder
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Websitedgelyza
 
Designing A Time bound resource download URL
Designing A Time bound resource download URLDesigning A Time bound resource download URL
Designing A Time bound resource download URLRuncy Oommen
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesMd Hossain Ali
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintMahmoud Rabie
 
OpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureOpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureEric D. Schabell
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1DianaGray10
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxUdaiappa Ramachandran
 

Dernier (20)

Cybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptxCybersecurity Workshop #1.pptx
Cybersecurity Workshop #1.pptx
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
 
Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1Secure your environment with UiPath and CyberArk technologies - Session 1
Secure your environment with UiPath and CyberArk technologies - Session 1
 
UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8UiPath Studio Web workshop series - Day 8
UiPath Studio Web workshop series - Day 8
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
 
9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond Ontologies
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdf
 
201610817 - edge part1
201610817 - edge part1201610817 - edge part1
201610817 - edge part1
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
 
COMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a WebsiteCOMPUTER 10 Lesson 8 - Building a Website
COMPUTER 10 Lesson 8 - Building a Website
 
Designing A Time bound resource download URL
Designing A Time bound resource download URLDesigning A Time bound resource download URL
Designing A Time bound resource download URL
 
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just MinutesAI Fame Rush Review – Virtual Influencer Creation In Just Minutes
AI Fame Rush Review – Virtual Influencer Creation In Just Minutes
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership Blueprint
 
OpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability AdventureOpenShift Commons Paris - Choose Your Own Observability Adventure
OpenShift Commons Paris - Choose Your Own Observability Adventure
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptx
 

Quality of Sensory Experience (QuaSE)

  • 1. Slides: http://www.slideshare.net/christian.timmerer Quality of Experience beyond Audio- Visual: Sensory Experience (QuaSE) Christian Timmerer Alpen-Adria-Universität Klagenfurt (AAU)  Faculty of Technical Sciences (TEWI)  Department of Information Technology (ITEC)  Multimedia Communication (MMC)  Sensory Experience Lab (SELab) blog.timmerer.com  selab.itec.aau.at  dash.itec.aau.at christian.timmerer@itec.aau.at 5th European Workshop on Visual Information Processing (EUVIP’14) December 10, 2014 Acknowledgments. This work was supported in part by the European Commission in the context of the NoE INTERMEDIA (NoE 038419), the P2P-Next project (FP7-ICT-216217), the ALICANTE project (FP7-ICT-248652), the SocialSensor project (FP7-ICT-287975), and the COST Action IC1003 QUALINET. Change log: - Dec’14: EUVIP’14, Paris, France - Oct’14: QUALINET Final Workshop, Delft, The Netherlands
  • 2. Sensory Experience • Consumption of multimedia content may stimulate also other senses – Vision or hearing [incl. emotion, sensation] – Olfaction, mechanoreception, thermoception, … • Annotation with metadata providing so-called sensory effects that steer appropriate devices capable of rendering these effects 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 2
  • 3. Sensory Experience • Consumption of multimedia content may stimulate also other senses – Vision or hearing [incl. emotion, sensation] – Olfaction, mechanoreception, thermoception, … • Annotation with metadata providing so-called sensory effects that steer appropriate devices capable of rendering these effects … giving her/him the sensation of being part of the particular mulsemedia ➪ worthwhile, informative user experience 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 3
  • 4. General Principle – Outline • General principle: there is a need for a scientific framework to capture, measure, quantify, judge, and explain the quality of (sensory) experience • Outline – [How to create, deliver, consume?] – How to capture and measure? – How to quantify? – How to judge and explain? 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 4
  • 5. How to create, delivery, consume? • Sensory Effect Description Language (SEDL) – Basic building blocks to describe, e.g., light, wind, fog, vibration, scent – MPEG-V Part 3, Sensory Information: Effects, GroupOfEffects – Adopted MPEG-21 DIA tools for adding time information (synchronization) • Description conforming to SEDL :== Sensory Effect Metadata (SEM) – Can be associated to any kind of multimedia content (e.g., movies, music, Web sites, games) – Support to be included in file (MP4) and transport (M2TS) formats • Tool support for creating (annotation tools) and consumption (players, Web plugins) ➜ selab.itec.aau.at • Devices: e.g., amBX (Ambient Experience) system + SDK, Gameskunk, Scentscape, etc. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 5
  • 6. How to capture and measure? • Subjective quality assessments – Methodology: based on standard methods – Test content: different genres, manually annotated (cf. QUALINET DB) • Experiment I – Aim: Demonstrate sensory effects as a vital tool for enhancing the quality of experience depending on the actual genre • Experiment II – Aim: investigate the relationship of the QoE to various video bit-rates of multimedia contents annotated with sensory effects. – Subjective quality gap between video resources annotated with and without sensory effects at different bit-rates • [Experiment III] ambient lights & different color calculation settings • Experiment IV – Aim: investigate the enhancement of the QoE and how users’ emotions are elicited and influenced by Web videos annotated with and without sensory effects 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 6
  • 7. Experiment II: Results Test Sequences Sequence Babylon A.D. Earth Duration 35s 21s Resolution 1280 x 544 1280 x 720 Motion High Low Nr. of Effects W: 7; V: 9 W: 8; V: 1 Bit-rates Kbit/s PSNR Kbit/s PSNR Low Quality 2154 38.93 2204 38.11 Medium Quality 3112 41.27 3171 40.65 High Quality 4044 42.95 4116 42.27 Highest Quality 6315 N/A 6701 N/A MOS vs. PSNR/bit-rate for Earth. M. Waltl, C. Timmerer H. Hellwagner, "Increasing the User Experience of Multimedia Presentations with Sensory Effects," WIAMIS’10, Desenzano del Garda, Italy, April 2010. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 7
  • 8. How to quantify? • Experiment V – Aim: towards a quality/utility model for QuaSE • Stimuli with all combinations of sensory effects – Vibration higher impact than light & wind – Highest QoE with all effects present • General QuaSE model C. Timmerer, B. Rainer, M. Waltl, "A Utility Model for Sensory Experience," QoMEX’13, Klagenfurt, Austria, 2013. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 8
  • 9. How to judge and explain? • Experiment VI – Aim: understand QuaSE • Biosensor-based QoE evaluation system J. Donley, C. Ritz, M. Shujau, "Analysing the Quality of Experience of Multisensory Media from Measurements of Physiological Responses,” QoMEX’14, Singapore, Sep. 2014. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 9
  • 10. How to judge and explain? • Experiment VII – Aim: understand QuaSE • EEG Correlates of Pleasant and Unpleasant Odor Perception E. Kroupi, A. Yazdani, J.-M. Vesin, T. Ebrahimi, "EEG Correlates of Pleasant and Unpleasant Odor Perception," ACM TOMM, vol. 11, no. 1s, Sep. 2014. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 10
  • 11. How to judge and explain? • Experiment VIII – Aim: understand QuaSE • Multiple-Scent Enhanced Multimedia Synchronization General temporal boundaries: -10s to +15s are “in-sync”, skew values beyond are “out-of-sync” N. Murray, B. Lee, Y. Qiao, and G.-M. Muntean, "Multiple-Scent Enhanced Multimedia Synchronization," ACM TOMM, vol. 11, no. 1s, Sep. 2014. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 11
  • 12. Conclusions • From the need for a scientific framework to capture, measure, quantify, judge, and explain the quality of experience • To … – How to create, deliver, consume? – How to capture and measure? – How to quantify? – How to judge and explain? • Open issues? ✔︎ ✔︎ ✔︎ ✔︎ Still Many! 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 12
  • 13. Open Issues / Challenges • QoE assessment is a delicate mixture of ingredients and choices – Test & lab environment – Test content – Test methodology – Data analysis • (Semi-)Automatic content creation/annotation • Towards large scale deployment – Lessons learnt from 3D (disaster) – 4D, 5D, xD – adding another dimension does not guarantee success • Holistic approach not feasible – Need for much more specialized QuaSE models 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 13
  • 14. Assessing Quality of Experience … A Bit Like Measuring ‘Happiness’ … © F. Pereira, Instituto Superior Técnico, Univ. Lisboa, Portugal 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 14
  • 15. Sensory Experience Lab http://selab.itec.aau.at/ Software and Services Standardization Publications Media Funding 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 15
  • 16. References • Markus Waltl, Christian Timmerer, Hermann Hellwagner, “A Test-Bed for Quality of Multimedia Experience Evaluation of Sensory Effects”, Proceedings of the First International Workshop on Quality of Multimedia Experience (QoMEX 2009), San Diego, USA, July 29-31, 2009. • C. Timmerer, J. Gelissen, M. Waltl, H. Hellwagner, “Interfacing with Virtual Worlds”, Proceedings of the NEM Summit 2009, Saint-Malo, France, September 28-30, 2009. • M. Waltl, C. Timmerer H. Hellwagner, “Increasing the User Experience of Multimedia Presentations with Sensory Effects”, Proceedings of the 11th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS’10), Desenzano del Garda, Italy, April 12-14, 2010. • M. Waltl, C. Timmerer, H. Hellwagner, “Improving the Quality of Multimedia Experience through Sensory Effects”, Proceedings of the 2nd International Workshop on Quality of Multimedia Experience (QoMEX2010), Trondheim, Norway, June 21-23, 2010. • C. Timmerer, M. Waltl, B. Rainer, H. Hellwagner, “Assessing the Quality of Sensory Experience for Multimedia Presentations”, Signal Processing: Image Communication, 2012. • M. Waltl, C. Timmerer, B. Rainer, H. Hellwagner, ”Sensory Effects for Ambient Experiences in the World Wide Web”, Multimedia Tools and Applications (MTAP), 2012. • B. Rainer, M. Waltl, Eva Cheng, Muawiyath Shujau, C. Timmerer, Stephen Davis, Ian Burnett, Christian Ritz, H. Hellwagner, ”Investigating the Impact of Sensory Effects on the Quality of Experience and Emotional Response in Web Videos”, Proceedings of 4th Int’l. Workshop on Quality of Multimedia Experience (QoMEX2012), 2012. • M. Waltl, C. Timmerer, B. Rainer, H. Hellwagner, “Sensory Effect Dataset and Test Setups”, Proceedings of 4th Int’l. Workshop on Quality of Multimedia Experience (QoMEX2012), 2012. • C. Timmerer, B. Rainer, M. Waltl, “A Utility Model for Sensory Experience”, In Proceedings of the 5th International Workshop on Quality of Multimedia Experience (QoMEX2013), 2013. • J. Donley, C. Ritz, M. Shujau, “Analysing the Quality of Experience of Multisensory Media from Measurements of Physiological Responses,” In Proceedings of the 5th International Workshop on Quality of Multimedia Experience (QoMEX2014), Singapore, 2014. • E. Kroupi, A. Yazdani, J.-M. Vesin, T. Ebrahimi, "EEG Correlates of Pleasant and Unpleasant Odor Perception," ACM TOMM, vol. 11, no. 1s, Sep. 2014. • N. Murray, B. Lee, Y. Qiao, and G.-M. Muntean, "Multiple-Scent Enhanced Multimedia Synchronization," ACM TOMM, vol. 11, no. 1s, Sep. 2014. • G. Ghinea, C. Timmerer, W. Lin, and S. R. Gulliver. "Mulsemedia: State of the Art, Perspectives, and Challenges," ACM TOMM, vol. 11, no. 1s, Sep. 2014. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 16
  • 17. Thank you for your attention ... questions, comments, etc. are welcome … Assoc-Prof. Dipl.-Ing. Dr. Christian Timmerer Klagenfurt University, Department of Information Technology (ITEC) Universitätsstrasse 65-67, A-9020 Klagenfurt, AUSTRIA christian.timmerer@itec.uni-klu.ac.at http://research.timmerer.com/ Tel: +43/463/2700 3621 Fax: +43/463/2700 3699 © Copyright: Christian Timmerer 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 17
  • 18. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 18
  • 19. 2014/12/10 Christian Timmerer, Alpen-Adria-Universität, Austria 19

Notes de l'éditeur

  1. Mulsemedia := multiple sensorial media
  2. Mulsemedia := multiple sensorial media