1. Czech Technical University in Prague
Faculty of Electrical Engineering
Overview of Qualinet
multimedia databases
Karel Fliegel
fliegek@fel.cvut.cz
Colloquium on Quality of Experience in Multimedia Systems and Services
23rd November 2012, Alpen-Adria-Universität Klagenfurt, Austria
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2. Qualinet WG4
Databases and Validation
• Success of developments in QoE largely depends
on availability of proper multimedia content
• Objectives of WG4*
– Create a rich and internationally recognized database of
content of different sorts
– Sharing such a database with the scientific community
• Leader
– Christian Timmerer (Alpen-Adria-Universität Klagenfurt)
• Deputies
– Karel Fliegel (CTU in Prague) – Databases
– Markus Barkowsky (Université de Nantes) – Validation
– Shelley Buchinger (Universität Wien) – Validation
* http://www.qualinet.eu/
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3. Qualinet Databases
• Resources for Qualinet Databases
– Description of multimedia databases
• Description of 114 MM databases on 79 pages
– Based on literature/Internet search and input from Qualinet
partner laboratories
– About 64 database owners
» About 17 of them Qualinet partner laboratories
– Mostly image (~50) or video datasets (~66), with (~55) or w/o
subjective quality rating
– Special content, e.g. 3D (~22), FV, Eyetracking (~21)
– Audio, Audiovisual, HDR and other modalities
» Qi0241.doc, QUALINET Multimedia Databases v3.5*
– List of multimedia databases
• Searchable list of databases in a spreadsheet
» Qi0242.xlsx, List of QUALINET Multimedia Databases v3.5*
* http://dbq.multimediatech.cz/
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4. Qualinet Databases
• Classification of Qualinet Databases
QUALINET Multimedia Databases v3.5, November 2012 (114, Q 55)
Annotated Multimedia Quality Databases (69, Q 50) Other Databases (45, Q 9)
Image Databases (13, Q 1)
Annotated Image Quality Databases (22, Q 15)
Video Databases (13, Q 3)
Annotated Video Quality Databases (25, Q 24)
3D Visual Content Databases (16, Q 2)
Eyetracking Databases (22, Q 9)
Audiovisual Databases (3, Q 2)
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5. Qualinet Databases
• Qualinet partners active in DB creation
Alpen‐Adria‐Universität Klagenfurt (2) Mid Sweden University (1)
Blekinge Institute of Technology (2) RMIT University (1)
Brno University of Technology (1) TU Berlin (1)
EPFL (6) TU Delft (5)
INSA Lyon (2) TU München (3)
Instituto de Optica (1) University of Beira Interior (1)
IRCCyN/IVC (24) University of Plymouth (3)
IT‐IST Lisbon (1) University of Toyama (1)
LaBRI (1)
– DB lists also content from outside Qualinet
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6. Qualinet Databases
• Qualinet Databases Online
– Qualinet’s main resource for sharing of the
datasets
• Available to Qualinet members and scientific
community
• Beta release currently available*
– Testing of the functionality by WG4 members
– Limited access for general scientific community
– Proposed development stages
• The first public version of the “Qualinet Databases”
offering core documents at simple wiki first quarter of
2012
• The fully functional version available by the end of 2012
* http://dbq-devel.multimediatech.cz/
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7. Qualinet Databases
• Qualinet Databases – beta release
– Simple living wiki page
http://dbq.multimediatech.cz/
– Information about the implementation process
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8. Qualinet Databases
• Qualinet Databases – beta release
– Beta release available for testing
http://dbq-devel.multimediatech.cz/
– Databases accessible to registered users
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9. Qualinet Databases
• Qualinet Databases – beta release
– Beta release available
• Everyone is welcome to register
• Pending registration requests are subject to approval by
administrators (WG4 leader, deputies)
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10. Qualinet Databases
• Qualinet Databases – beta release
– Functionality overview
» Qi0243.doc, QUALINET Multimedia Databases Online v1.0*
• Browsing the databases
– List available to all registered users
– Access to multimedia content for Qualinet members
• Editing the databases
– Description can be edited by the Database Owner
• New database submission
– Submission to be approved by admin
• Tracking database usage
• Call for new datasets
* http://dbq.multimediatech.cz/
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11. Qualinet Databases
• Qualinet Databases – beta release
– Hosting of the Databases
• Content hosted by the Database Owner
– Hybrid solution in mid-term
– Basic HW/SW requirements
• Content hosted in Qualinet Databases
– Self-hosting of Qualinet databases in long-term
– Advanced HW/SW requirements
– FTP access requested while entering new dataset
• New dedicated HW solution at the CTU in Prague
– New server to be ready for the fully functional release
– HP Proliant server, disk array (24TB)
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12. Qualinet Databases
• Qualinet Databases – beta release
– Overview and further steps
• Beta release for testing accessible
– http://dbq-devel.multimediatech.cz/
• Living wiki page to publish updates
– http://dbq.multimediatech.cz/
• Fully functional release by the end of 2012
– Linked to subdomain (db.qualinet.eu)
– Button will be added to the Qualinet homepage
• Feedback from registered users
– All comments and requests will be considered
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13. Qualinet DB Examples
• IRCCyN/IVC databases
– Image Datasets*
Database Type MOS Other
IRCCyN/IVC3D images dataset 3D Image YES
IRCCyN/IVC "Broken Arrows" database Image YES
IRCCyN/IVC DIBR Images Database Image YES
IRCCyN/IVC DWTvsDTCWT DB Image YES
IRCCyN/IVC Enrico database Image YES
IRCCyN/IVC Eyetracker 2006 05 Image NO Eyetracking
IRCCyN/IVC Eyetracker data for the Berkeley segmentation dataset Image NO Eyetracking
IRCCyN/IVC Fourier Subband database Image YES
IRCCyN/IVC Image Quality Database Image YES
IRCCyN/IVC LAR database Image YES
IRCCyN/IVC Scores on Toyama (MICT) Database Image YES
IRCCyN/IVC Selective Encryption database Image YES
* http://dbq-devel.multimediatech.cz/
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14. Qualinet DB Examples
• IRCCyN/IVC databases
– Video Datasets*
Database Type MOS Other
IRCCyN/IVC NAMA3DS1 ‐ COSPAD1 3D Video YES
IRCCyN/IVC 1080i Database Video YES
IRCCyN/IVC Eyetracker SD 2008 11 Database Video NO Eyetracking
IRCCyN/IVC Eyetracker SD 2009_12 Database Video YES Eyetracking
IRCCyN/IVC H264 AVC vs SVC VGA Video Database Video YES
IRCCyN/IVC H264 HD vs Upscaling and Interlacing Video database Video YES
IRCCyN/IVC Influence Content Video VGA database Video YES
IRCCyN/IVC JEG264HMIX1 database Video YES
IRCCyN/IVC SD RoI Database Video YES
IRCCyN/IVC SVC4QoE QP0 QP1 Video Database Video YES
IRCCyN/IVC SVC4QoE Replace Slice Video Database Video YES
IRCCyN/IVC SVC4QoE Temporal Switch Video Database Video YES
* http://dbq-devel.multimediatech.cz/
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15. Qualinet DB Examples
• IRCCyN/IVC databases
– Selected Image Datasets*
Database IRCCyN/IVC Still Image LAR coded art images IRCCyN/IVC‐Toyama IRCCyN/IVC DIBR Images
(LCD)
Resolution 512x512 512x512 768x512 1024x768
Methodology DSIS DSIS ACR ACR and Pair
Comparison
Degradation type JPEG, JPEG2000, LAR JPEG, JPEG2000, LAR JPEG, JPEG2000, LAR DIBR (depth image‐
coding and blurring coding coding based rendering)
Number of observers 15 20 27 43
Observers type expert expert naive naive
Number of images 235 120 196 96
Rejection method / / VQEG MM Test plan VQEG MM Test plan
Observation distance 6H 6H 4H 4H
Display CRT CRT LCD DELL 1704FPT LCD TvLogic LVM401
Luminance / / 0.3 / 180 cd/m² 0.1 ‐ 180 cd/m²
Duration / / 30 minutes 20 (ACR) + 40 (PC) mins
* http://www.irccyn.ec-nantes.fr/spip.php?article491&lang=fr
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16. Qualinet DB Examples
• IRCCyN/IVC databases
– Selected Video Datasets*
Database Videos Eyetracker SD ROI SVC4QoE SVC4QoE SVC4QoE H264 AVC vs H264 HD vs IRCCyN/IVC VQEG HDTV JEG264HMIX
1080i SD 2009 12 Replace QP0 QP1 Temporal AVC Upscaling Influence Pool2 1
Slice Switch and Content
Interlacing
* http://www.irccyn.ec-nantes.fr/spip.php?article491&lang=fr
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17. Database Videos Eyetracker SD ROI SVC4QoE SVC4QoE SVC4QoE H264 AVC vs H264 HD vs IRCCyN/IVC VQEG HDTV JEG264HMIX
1080i SD 2009 12 Replace QP0 QP1 Temporal AVC Upscaling Influence Pool2 1
Slice Switch and Content
Qualinet DB Examples
Interlacing
Resolution HD SD SD VGA VGA VGA QVGA HD VGA HD HD
(1920x1080) (720x576) (720x576) (640x480) (640x480) (640x480) (320x240) (1920x1080) (640x480) (1920x1080) (1920x1080)
and VGA
(640x480)
Display Mode interlaced interlaced interlaced progressive progressive progressive progressive progressive progressive interlaced progressive
• IRCCyN/IVC databases
Methodology ACR and ACR ACR ACR ACR ACR SAMVIQ ACR ACR ACR ACR
SAMVIQ
Degradation H.264 – Selected Video Datasets
H.264 H.264 H.264 and H.264 and H.264 and H.264 and H.264 H.264/SVC H.264 H.264
type H.264/SVC H.264/SVC H.264/SVC H.264/SVC
Transmission No Partially Partially Partially No No No No No Partially Partially
Errors (Simulated) (Simulated) (Simulated) (Simulated) (Simulated)
Number of 28 30 25 29 27 28 15 26 29 24 27
observers
observers naive naive naive naive naive naive naive naive naive naive naive
type
Number of 192 100 84 135 324 390 56 87 300 168 160
videos
Rejection PQ VQEG MM EBU VQEG MM VQEG MM VQEG MM ITU VQEG MM VQEG MM VQEG HDTV VQEG HDTV
method Test plan Test plan Test plan Test plan Test plan Test plan Test plan Test plan
Observation 3H 6H 6H 4H 4H 4H 6H (QVGA) 3H 4H 3H 3H
distance and 4H
(VGA)
Display LCD Philips LCD TV Logic CRT JVC DT‐ LCD TV Logic LCD TV Logic LCD TV Logic CRT LCD TV Logic LCD TV Logic LCD TV Logic LCD TV Logic
T370 HW01 LVM401 V1910CG LVM401 LVM401 LVM401 Samsung LVM401 LVM401 LVM401 LVM401
SyncMaster
1100MB
Luminance 0.65 / 0.16 / 0.67 / 0.1 / 180 0.1 / 180 0.1 / 180 1 / 150 0.16 / 200 0.1 / 180 0.16 / 200 0.1 / 180
450cd/m² 200cd/m² 70cd/m² cd/m² cd/m² cd/m² cd/m² cd/m² cd/m² cd/m² cd/m²
Duration 60 minutes 45 minutes 30 minutes 40 minutes 2x50
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2x60 25 minutes 45 minutes 45 minutes
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18. Qualinet DB Examples
• IRCCyN/IVC databases
– Selected 3D datasets*
Database 3D Images Database NAMA3DS1 NAMA3DS1 ‐ COSPAD1
2008
Videos / Images Images Videos Videos
Resolution (per view) 512x512 1920x1080 1920x1080
display mode 3D / 3D
Methodology SAMVIQ / ACR
Degradation type JPEG/J2K/Blur symmetric / H.264/JPEG2000/spatial
Transmission Errors No / No
Number of observers 19 / 29
observers type naive / naive
Number of 96 10 110
images/videos
Rejection method VQEG Multimedia / VQEG HDTV testplan
Tesplan
Observation distance 4H / 3H
Display CRT / LCD Philips 46PFL9705H
Luminance 0.3 / 120cd/m² / 180cd/m²
Duration 30 minutes / 45 minutes
* http://www.irccyn.ec-nantes.fr/spip.php?article493
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19. Qualinet DB Examples
• IRCCyN/IVC databases
– Selected 3D displays at IVC*
• Autostereoscopic displays
– Alioscopy (8 views, lenticular)
– Philips 3D Wow (9 views, lenticular)
– Holografika (holographic screen)
• Passive (polarized glasses) stereoscopic displays
– Panasonic BT-3DL2550 Professional (1920x1080)
– Zalman Trimon ZM-M220W (1920x1080)
• Active (shutter glasses) stereoscopic displays
– Projector JVC DLA X7 (1920x1080)
– Panasonic TX-P46VT20E 46" (1920x1080)
– 2 x Philips 46PFL9705H 46" (1920x1080)
– BenQ XL2410T (1920x1080)
– Alienware OptX AW2310 (1920x1080)
– Samsung SyncMaster 2233RZ (1680x1050) * http://www.irccyn.ec-nantes.fr/spip.php?article493
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20. Qualinet DB Examples
• IRCCyN/IVC databases
– Selected Eye-tracking datasets*
Database Eyetracker 2006 05 Eyetracker Berkeley IRCCyN/IVC Eyetracker SD 2008 Eyetracker SD 2009
Eyetracker Ims LIVE 11 12
Videos / Images Images Images Images Videos Videos
Resolution 512x512 to 768x512 481x321 512x512 to 768x512 SD (720x576) SD (720x576)
display mode progressive progressive progressive interlaced interlaced
Methodology Free task Free task Free task Free task ACR
Degradation type No degradation No degradation No degradation H.264 H.264
Transmission Errors No No No No Partially (Simulated)
Number of observers 40 25 21 37 30
observers type naive naive naive naive naive
Number of 27 80 29 51 100
images/videos
Rejection method / / / / VQEG MM Test plan
Observation distance 4H (of the screen) 6H 70cm 6H 6H
Display CRT CRT JVC DT‐V1910CG Dell 1905FP LCD Philips T370 LCD TV Logic LVM401
HW01
Luminance / 0.67 / 70cd/m² 0.16 / 200 cd/m² 0.65 / 450cd/m² 0.16 / 200cd/m²
Duration / 30 minutes 15 minutes 15 minutes 45 minutes
* http://www.irccyn.ec-nantes.fr/spip.php?article539
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21. Qualinet DB Examples
• IRCCyN/IVC databases
– Selected Eye-tracking equipment*
• Eye-trackers
– (1) Binocular, 500Hz with 3D content
– (2) Monocular, 50Hz with HD content
– (3) Monocular, 1250Hz system
– (4) Head-mounted system
– (5) Binocular, 60Hz Remote system
(1) Binocular (2) Monocular (3) Monocular (4) Head‐mounted (5) Binocular‐remote
* http://www.irccyn.ec-nantes.fr/spip.php?article539
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22. Qualinet DB Examples
• IRCCyN/IVC databases
– NAMA3DS1 – COSPAD1*
• 110 3D stereoscopic videos with subjective results
• Reference plus 10 different degradations (HRC)
• 10 different source video sequences (SRC)
• Proposed for evaluation of different viewing condition
and observer distributions in international laboratories
* http://www.irccyn.ec-nantes.fr/spip.php?article1052
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23. Qualinet DB Examples
• IRCCyN/IVC databases
– NAMA3DS1 – COSPAD1*
* http://www.irccyn.ec-nantes.fr/spip.php?article1052
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24. Qualinet DB Examples
• IRCCyN/IVC databases
– Influence Content Video VGA database*
• Contains 300 video sequences with subjective results
• 20 different degradations (HRC) – SVC scenarios
• 60 different source video sequences (SRC)
• Proposed for evaluation of quality dependencies on
the encoded source content
* http://www.irccyn.ec-nantes.fr/spip.php?article771
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25. Qualinet DB Examples
• IRCCyN/IVC databases
– SVC4QoE Temp Switch Video VGA database*
• Contains 390 video sequences with subjective results
• 36 different degradations (HRC) – (H.264, H.264/SVC)
• 11 different source video sequences (SRC)
• Proposed for analysis of spatial scalability feature of
SVC for error concealment
* http://www.irccyn.ec-nantes.fr/spip.php?article770
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26. Qualinet DB Examples
• IRCCyN/IVC databases
– Eyetracker SD 2009_12 Database*
• Contains eyetracker data and 100 associated videos
• Various content, reference and 4 error transmission
• 20 different source video sequences
Reference Saliency information Distortion A Distortion B
• Proposed for analysis of saliency awareness for
objective video quality assessment
* http://www.irccyn.ec-nantes.fr/spip.php?article550
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27. Qualinet DB Examples
• EPFL MMSPG databases
– Image and Video Datasets*
Database Type MOS Other
MMSPG 3D Image Quality Assessment Database 3D Image YES
MMSPG 3D Video Quality Assessment Database 3D Video YES
MMSPG JPEG XR image compression database Image YES
EPFL‐PoliMI Video Quality Assessment Database Video YES
MMSPG Scalable Video Database Video YES
* http://dbq-devel.multimediatech.cz/
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28. Qualinet DB Examples
• EPFL MMSPG databases
– Selected equipment*
• Screens
– Professional 2D screens (Eizo CG301W)
» 30”, 2560x1600, wide color gamut
– 4K screen (Sony SRML560)
» 56”, QHD 3840x2160
– Stereoscopic screen (Hyundai S465D)
» 46”, 1920x1080, polarized
– Autostereoscopic screen (Dimenco BDl5231V-3D2R)
» 52”, 1920x1080, 28 views, image + depth
• Powerful video servers
• EEG, eyetracker * http://mmspg.epfl.ch/
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29. Qualinet DB Examples
• EPFL MMSPG databases
– JPEG XR Image Compression Database*
• Compares new JPEG XR to JPEG and JPEG 2000
– Performance evaluation of codecs in HiRes images
– 6 images (24 BPP, 1280x1600), 3 image codecs (JPEG,
JPEG 2000, JPEG XR), Both 4:4:4 and 4:2:0 encoding
– Original images, Encoded images (training, testing)
– Raw subjective scores, Mean opinion scores and CIs
* http://jahia-prod.epfl.ch/site/mmspl/op/edit/page-58334.html
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30. Qualinet DB Examples
• EPFL MMSPG databases
– Scalable Video Database*
• Extensive subjective tests for SVC with 3 HD contents
– 320x180, 640x360, 1280x720, 6.25, 12.5, 25, 50 fps
– Bitrates ranging from 300 kbps to 4 Mbps
– Stimulus comparison, simultaneous side by side playback
– Original videos, encoded videos and decoders
– Subjective scores
* http://mmspg.epfl.ch/svd
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31. Qualinet DB Examples
• EPFL MMSPG databases
– 3D Image Quality Assessment Database*
• Influence of acquisition parameters on image quality
– 10 scenes, 5 camera distances
– Single stimulus (SSCQS), 5 quality levels, 17 subjects
– Captured left and right images, stereo image pairs
– Subjective quality scores, mean opinion scores and CI
* http://mmspg.epfl.ch/cms/page-58394.html
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32. Qualinet DB Examples
• EPFL MMSPG databases
– 3D Video Quality Assessment Database*
• Influence of acquisition parameters on 3D video quality
– 6 scenes, 5 camera distances
– Single stimulus (SSCQS), 5 quality levels, 17 subjects
– Processed and encoded stereo video pairs
– Subjective quality scores, mean opinion scores and CI
* http://mmspg.epfl.ch/cms/page-58395.html
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33. Qualinet DB Examples
• TU Delft databases
– TU Delft Eye-Tracking Release 1 & 2*
• Saliency analysis for LIVE image database
– In R1 29 source images, 20 participants, free viewing
– In R2 two different tasks (task effect on saliency)
» Free viewing (as if looking at a photo album)
» Quality assessment
Saliency map ROI
* http://mmi.tudelft.nl/iqlab/eye_tracking_1.html, http://mmi.tudelft.nl/iqlab/eye_tracking_2.html
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34. Qualinet DB Examples
• TU Delft databases
– Video Task Effect Eye-Tracking*
• Saliency analysis for 25 video segments (20s each)
– Video segments extracted from action based movies
» Two distorted versions produced (H.264)
– Two different tasks (task effect on saliency)
» Free viewing
» Quality assessment
* http://mmi.tudelft.nl/iqlab/video_task_eye_tracking_1.html
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35. Qualinet DB Examples
• TU München databases
– 1080p50 Dataset*
• Subjective test results for 1080p50 video sequences
– Five different HDTV 1080p50 video sequences
– 20 encoded sequences with H.264/AVC (2-40MBit/s)
– Four scenarios
» Reference monitor (Sony BVM-L230, 23")
» Consumer LCD display (Sony KDL-55X4500, 56")
» LCoS Projector (JVC DLA-HD750, 2.8m)
» LCoS Projector & 7.1 surround sound (JVC DLA-HD750, 2.8m)
Reference monitor LCD‐TV Projector
* http://www.ldv.ei.tum.de/en/research/videolab/data-sets-downloads/tum-1080p50-data-set/
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36. Qualinet DB Examples
• AAU Klagenfurt
– Sensory Experience Dataset*
• Annotation with metadata providing so-called sensory
effects that steer appropriate devices capable of
rendering these effects
* http://selab.itec.aau.at/software-and-services/dataset/
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37. Qualinet DB Examples
• Examples of Qualinet Databases
– Established dataset track at QoMEX’12*
• Keimel at al, The TUM High Definition Video Datasets
• Pitrey et al, Using Overlapping Subjective Datasets to
Assess the Performance of Objective Quality Metrics on
Scalable Video Coding and Error Concealment
• Urvoy et al, NAMA3DS1-COSPAD1: Subjective video
quality assessment database on coding conditions
introducing freely available high quality 3D
stereoscopic sequences
• M. Waltl et al, Sensory Effect Dataset and Test Setups
– To be continued at QoMEX’13**
* http://www.qomex2012.org/ , ** http://www.qomex2013.org/
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38. Conclusions
• Qualinet Databases
– Database of content of different sorts
– Please register to our online tool
• Beta release for testing
– http://dbq-devel.multimediatech.cz/
• Living wiki page to publish updates
– http://dbq.multimediatech.cz/
• Other issues
– Using Qualinet Databases functionality
• Tracking database usage
• Call for new datasets
– White paper
» Qi0244.doc, Karel Fliegel and Christian Timmerer, QUALINET
MULTIMEDIA DATABASE
ENABLING QOE EVALUATIONS AND BENCHMARKING v1.0*
* http://dbq.multimediatech.cz/
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39. Czech Technical University in Prague
Faculty of Electrical Engineering
Thank you for your attention
fliegek@fel.cvut.cz
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