VQMT3D Project: Report 11 on 3D-video Quality Analysis

In cooperation with IITP RAS

About the Report

We present the eleventh report of the Video Quality Measurement Tool for 3D (VQMT3D) project, in which we provide a technical-quality analysis of selected Chinese S3D movies in comparison with Hollywood ones using a wide range of stereoscopic quality metrics.

We selected 10 Chinese S3D movies released from 2011 to 2016 and analyzed them with 6 measurable metrics and 4 qualitative metrics from our metric list. Detailed visualizations and notes are provided for each of the analyzed movies.

Analysed films

Measurable metrics

Qualitative metrics

  • Flying Swords of Dragon Gate
  • Painted Skin: The Resurrection
  • Young Detective Dee: Rise of the Sea Dragon
  • The Monkey King
  • The White Haired Witch of Lunar Kingdom
  • Dragon Blade
  • Zhongkui: Snow Girl and the Dark Crystal
  • Monster Hunt
  • The Monkey King: The Legend Begins
  • Mermaid
  • Depth Budget
  • Scale Mismatch
  • Rotation Mismatch
  • Vertical Parallax
  • Color Mismatch
  • Sharpness Mismatch
  • Edge-Sharpness Mismatch
  • Occlusion Processing
  • Cardboard Effect
  • Stuck-to-background objects

Report contents and diagram examples

The report consists of 3 main parts:

In the beginning we explain how to interpret metric values and describe the measurement units. Measurable metrics (horizontal disparity, geometric inconsistencies, color and sharpness mismatch) provide values that can be compared numerically. For qualitative metrics only frame visualizations are included. The various charts and visualizations are also described in this section.

The next section of the report presents overall comparison charts with averaged results for measurable metrics. We use four types of charts: the first two are scatterplots, showing average metric value versus movie release date or budget. The third type of chart is a barchart, allowing easier ranking of movies. The fourth type provides more detailed comparison, as it shows the distribution of high and low-quality scenes. The plots contain data for Hollywood movies and selected Chinese movies.


An example bar chart showing depth budget of the selected Chinese movies.

An example overall plot illustrating average vertical prallax of movies with respect to release date.

An example of color mismatch metric visualization. The checkerboard shows the global difference of color between left and right views.

An example of rotation mismatch visualization.

The largest part of the report contains detailed analysis with per-frame visualizations for both measurable and qualitative metrics, and notes for each of the 10 Chinese S3D movies.

Our measurements focus mostly on technical quality. We don’t claim to compare “user experience”. Nevertheless, the quality of the user experience should correlate with the film’s technical quality.

Publications

If you want to make a reference to this project, please refer to one of the following publications:

  1. Mikhail Erofeev, Dmitriy Vatolin, Alexander Voronov, Alexey Fedorov,
    “Toward an Objective Stereo-Video Quality Metric: Depth Perception of Textured Areas,”
    International Conference on 3D Imaging,
    2012. doi:10.1109/IC3D.2012.6615120 (download)
  2. Dmitriy Akimov, Alexey Shestov, Alexander Voronov, Dmitriy Vatolin,
    “Automatic Left-Right Channel Swap Detection,”
    International Conference on 3D Imaging,
    2012. doi:10.1109/IC3D.2012.6615126 (download)
  3. Alexander Voronov, Alexey Borisov, Dmitriy Vatolin,
    “System for automatic detection of distorted scenes in stereo video,”
    International Workshop on Video Processing and Quality Metrics for Consumer Electronic (VPQM-2012),
    pp. 138–143, 2012. (download)
  4. Alexander Voronov, Dmitriy Vatolin, Denis Sumin, Vyacheslav Napadovsky, Alexey Borisov,
    “Towards Automatic Stereo-video Quality Assessment and Detection of Color and Sharpness Mismatch,”
    International Conference on 3D Imaging,
    2012. doi:10.1109/IC3D.2012.6615121 (download)
  5. Alexander Voronov, Dmitriy Vatolin, Denis Sumin, Vyacheslav Napadovsky, Alexey Borisov,
    “Methodology for stereoscopic motion-picture quality assessment,”
    Proc. SPIE 8648, Stereoscopic Displays and Applications XXIV,
    vol. 8648, pp. 864810-1–864810-14, 2013. doi:10.1117/12.2008485 (download)
  6. Alexander Bokov, Dmitriy Vatolin, Anton Zachesov, Alexander Belous, Mikhail Erofeev,
    “Automatic detection of artifacts in converted S3D video,”
    Proc. SPIE 9011, Stereoscopic Displays and Applications XXV (March 6, 2014),
    vol. 901112, 2014. doi:10.1117/12.2054330 (download)
  7. Stanislav Dolganov, Mikhail Erofeev, Dmitriy Vatolin, Yury Gitman,
    “Detection of stuck-to-background objects in converted S3D movies,”
    2015 International Conference on 3D Imaging, IC3D 2015,
    2015. doi:10.1109/IC3D.2015.7391839 (download)
  8. Yury Gitman, Can Bal, Mikhail Erofeev, Ankit Jain, Sergey Matyunin, Kyoung-Rok Lee, Alexander Voronov, Jason Juang, Dmitriy Vatolin, Truong Nguyen,
    “Delivering Enhanced 3D Video,”
    Intel Technology Journal,
    vol. 19, pp. 162–200, 2015. (download)
  9. Dmitriy Vatolin, Alexander Bokov, Mikhail Erofeev, Vyacheslav Napadovsky,
    “Trends in S3D-Movie Quality Evaluated on 105 Films Using 10 Metrics,”
    Proceedings of Stereoscopic Displays and Applications XXVII,
    pp. SDA-439.1–SDA-439.10, 2016. doi:10.2352/ISSN.2470-1173.2016.5.SDA-439 (download)
  10. Alexander Bokov, Sergey Lavrushkin, Mikhail Erofeev, Dmitriy Vatolin, Alexey Fedorov,
    “Toward fully automatic channel-mismatch detection and discomfort prediction for S3D video,”
    2016 International Conference on 3D Imaging (IC3D),
    2016. doi:10.1109/IC3D.2016.7823462 (download)
  11. Dmitriy Vatolin, Sergey Lavrushkin,
    “Investigating and predicting the perceptibility protect of channel mismatch in stereoscopic video,”
    Moscow University Computational Mathematics and Cybernetics,
    vol. 40, pp. 185–191, 2016. doi:10.3103/s0278641916040075 (download)
  12. Anastasia Antsiferova, Dmitriy Vatolin,
    “The influence of 3D video artifacts on discomfort of 302 viewers,”
    2017 International Conference on 3D Immersion (IC3D),
    2017. doi:10.1109/IC3D.2017.8251897 (download)
  13. Dmitriy Vatolin, Alexander Bokov,
    “Sharpness Mismatch and 6 Other Stereoscopic Artifacts Measured on 10 Chinese S3D Movies,”
    Proceedings of Stereoscopic Displays and Applications XXVIII,
    pp. 137–144, 2017. doi:10.2352/ISSN.2470-1173.2017.5.SDA-340 (download)
  14. Sergey Lavrushkin, Vitaliy Lyudvichenko, Dmitriy Vatolin,
    “Local Method of Color-Difference Correction Between Stereoscopic-Video Views,”
    Proceedings of the 2018 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON),
    2018. doi:10.1109/3DTV.2018.8478453 (download)
  15. Aidar Khatiullin, Mikhail Erofeev, Dmitriy Vatolin,
    “Fast Occlusion Filling Method For Multiview Video Generation,”
    Proceedings of the 2018 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON),
    2018. doi:10.1109/3DTV.2018.8478562 (download)
  16. Sergey Lavrushkin, Dmitriy Vatolin,
    “Channel-Mismatch Detection Algorithm for Stereoscopic Video Using Convolutional Neural Network,”
    Proceedings of the 2018 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON),
    2018. doi:10.1109/3DTV.2018.8478542 (download)
  17. Alexander Ploshkin, Dmitriy Vatolin,
    “Accurate Method of Temporal Shift Estimation for 3D Video,”
    Proceedings of the 2018 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON),
    2018. doi:10.1109/3DTV.2018.8478431 (download)
  18. Sergey Lavrushkin, Konstantin Kozhemyakov, Dmitriy Vatolin,
    “Neural-Network-Based Detection Methods for Color, Sharpness, and Geometry Artifacts in Stereoscopic and VR180 Videos,”
    International Conference on 3D Immersion (IC3D),
    2020. doi:10.1109/IC3D51119.2020.9376385 (download)
  19. Kirill Malyshev, Sergey Lavrushkin, Dmitriy Vatolin,
    “Stereoscopic Dataset from A Video Game: Detecting Converged Axes and Perspective Distortions in S3D Videos,”
    International Conference on 3D Immersion (IC3D),
    2020. doi:10.1109/IC3D51119.2020.9376375 (download)
  20. Lavrushkin Sergey, Molodetskikh Ivan, Kozhemyakov Konstantin, Vatolin Dmitriy,
    “Stereoscopic quality assessment of 1,000 VR180 videos using 8 metrics,”
    Electronic Imaging, 3D Measurement and Data Processing,
    2021. doi:10.2352/issn.2470-1173.2021.2.sda-350 (download)

Reports overview

Stereo-analysis project homepage

Report 1 (S3D shooting quality analysis of 5 movies) Download
(Additional info for bloggers and press)
Pages: 246
Figures: 295
Report 2 (S3D shooting quality analysis of 5 movies) Download
(Additional info for bloggers and press)
Pages: 342
Figures: 442
Report 3 (2D-3D conversion quality analysis of 5 movies) Download
(Additional info for bloggers and press)
Pages: 305
Figures: 336
Report 4 (S3D shooting quality analysis of 5 movies) Download Pages: 301
Figures: 402
Report 5 (2D-3D conversion quality analysis of 5 movies) Download
(Additional info for bloggers and press)
Pages: 384
Figures: 404
Report 6 (Stereo Window analysis of 10 movies) Download
(Additional info for bloggers and press)
Pages: 415
Figures: 455
Report 7 (Stereo Window analysis of 10 movies) Download
(Additional info for bloggers and press)
Pages: 333
Figures: 348
Report 8 (Rotate Analysis, Temporal Shift, Channels Swap, Zoom Mismatch in 25 movies) Download
(Additional info for bloggers and press)
Pages: 366
Figures: 361
Report 9 (Temporal Shift, Stuck-to-Background Objects, 2D to S3D conversion in Captured Films) Download
(Additional info for bloggers and press)
Pages: 467
Figures: 529
Report 10 (Overall analysis of 105 movies) Download Pages: 211
Figures: 270
Report 11 (Overall analysis of 10 selected Chinese movies) Download Pages: 322
Figures: 566

Download

Full report (322 pages) is absolutely free but download is available only for industry professionals (due to publication of real mistakes in the post-production process).

To download the report, please fill-in the request form.
You will get the download link for all reports (Reports #1–11) via e-mail.

All materials in this evaluation are used for research purposes and in accordance with Fair Use conditions. This evaluation is not published widely, but it is available for free under a subscription for stereoscopy and cinema technology professionals.

Feedback

Do you have any feedback on previous reports? What did you find useful, or was anything lacking?

What would you like to see in future reports (analysis of certain films, different metrics, charts and visualizations, etc.)?

We are open to collaboration. If you are interested in working with us, please write your propositions:

Any other feedback that doesn't fit in previous fields:

Contacts

For questions and propositions please contact us 3dmovietest@graphics.cs.msu.ru

25 May 2021
See Also
PSNR and SSIM: application areas and critics
Learn about limits and applicability of the most popular metrics
MSU 3D-video Quality Analysis. Report 10
Detection of stereo window violation
How to find objects that are present only in one view?
Depth continuity estimation in S3D video
How smooth is the depth transition between scenes?
Detection of 3D movie scenes shot on converged axes
Another cause of headaches when watching 3D movies.
Parallax range estimation in S3D video
The parallax range should be both comfortable and entertaining for spectators.
Site structure