VQMT3D Project: Report 10 on 3D-video Quality Analysis
- Projects, ideas: Dr. Dmitriy Vatolin
- Implementation: Alexander Bokov, Stanislav Dolganov, Vitaliy Lyudvichenko, Vladimir Yanushkovsky, Vyacheslav Napadovsky, Denis Sumin, Alexander Voronov, Alexey Borisov, Alexander Belous, Alexey Shalpegin, Alexey Fedorov, Sergey Lavrushkin, Konstantin Kozhemiakov, Maxim Velikanov, Dmitriy Konovalchuk
In cooperation with IITP RAS
About the Report
This is the 10th Anniversary Report of the VQMT3D project. It contains a detailed analysis of 105 stereoscopic (S3D) movies. It has some significant differences from previous reports released by us.
- For the first time, the report contains overall charts of comparison of all movies by more than 10 metrics. Moreover, we show a new method for comparing films by presenting film ratings and highlighting the top in four different categories.
- This report is absolutely free and available without registration because it does not contain any copyright content.
- Our project received valuable support from professional stereographers. In total, we corresponded with about 100 stereographers, 32 of whom visibly contributed to our reports.
We are publishing this report almost four years after its creation due to several reasons. We’ve cooperated with multiple companies and organizations, but their support in recent years has dwindled to zero. Moreover, although several companies whose business depends heavily on the success of 3D movies promised to aid our efforts, these promises went unfulfilled. We’re nevertheless happy to finally present you with our 10th Anniversary Report.
Over 100 films analysed, including: |
Examined problems: |
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Report contents and diagram examples
Firstly, we present an overall comparison of the movies we evaluated. It includes charts depicting the average metric values relative to a movie’s release date and budget, as well as charts illustrating metric-value distributions.
An example diagram which compares the depth continuity metric value and budget for each movie. Higher values indicate more frequent and intense depth jump cuts throughout a film.
Color-mismatch values represent the strength of color difference between two views of a stereoscopic frame. An example bar-chart which shows average color-mismatch for each movie.
In the next section we rate movies on the basis of our metrics for multiple categories. Different metrics correspond to different categories, as do low- versus high-budget movies and movies with distinct release years. We also present an overall technical-quality comparison that combines all the relevant results for the various quality metrics.
An example overall movie rating with top 10 best movies in terms of stereo window placement comfort.
This example diagram shows the technical quality category of low-budget movies, which is based on average movie rating by each metric.
We sum up the ratings in the previous section by concisely listing movies by their total number of nominations.
The final part describes our plans for continuing this project.
Download report #10
Publications
If you want to make a reference to this project, please refer to one of the following publications:
- 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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
Feedback
Contacts
For questions and proposition please contact us 3dmovietest@graphics.cs.msu.ru
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MSU Benchmark Collection
- Video Colorization Benchmark
- Super-Resolution for Video Compression Benchmark
- Defenses for Image Quality Metrics Benchmark
- Learning-Based Image Compression Benchmark
- Super-Resolution Quality Metrics Benchmark
- Video Saliency Prediction Benchmark
- Metrics Robustness Benchmark
- Video Upscalers Benchmark
- Video Deblurring Benchmark
- Video Frame Interpolation Benchmark
- HDR Video Reconstruction Benchmark
- No-Reference Video Quality Metrics Benchmark
- Full-Reference Video Quality Metrics Benchmark
- Video Alignment and Retrieval Benchmark
- Mobile Video Codecs Benchmark
- Video Super-Resolution Benchmark
- Shot Boundary Detection Benchmark
- The VideoMatting Project
- Video Completion
- Codecs Comparisons & Optimization
- VQMT
- MSU Datasets Collection
- Metrics Research
- Video Quality Measurement Tool 3D
- Video Filters
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