BVI-HD: A Perceptual Video Quality Database for HEVC and Texture Synthesis Compressed Content

Fan Zhang, Felix Mercer Moss, Roland Baddeley and David Bull


This page introduces a new high definition video quality database, referred to as BVI-HD, which contains 32 reference and 384 distorted video sequences plus subjective scores. The reference material in this database was carefully selected to optimise the coverage range and distribution uniformity of five low level video features, while the included 12 distortions, using both original High Efficiency Video Coding (HEVC) and HEVC with synthesis mode (HEVC-SYNTH), represent state-of-the-art approaches to compression. The range of quantisation parameters included in the database for HEVC compression was determined by a subjective study, the results of which indicate that a wider range of QP values should be used than the current recommendation. The subjective opinion scores for all 384 distorted videos were collected from a total of 86 subjects, using a double stimulus test methodology. Based on these results, we compare the subjective quality between HEVC and synthesised content, and evaluate the performance of nine state-of-the-art, full-reference objective quality metrics. This database has now been made available online, representing a valuable resource to those concerned with compression performance evaluation and objective video quality assessment.


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[DOWNLOAD] all subjective data.

Please read the README file before using the data.

If this content has been mentioned/used in a research publication, please give credit to both CDVL and the University of Bristol, by referencing the following papers:

[1] Fan Zhang, Felix Mercer Moss, Roland Baddeley, and David, R. Bull, “BVI-HD: A Video Quality Database for HEVC Compressed and Texture Synthesised Content”, IEEE Trans. on Multimedia, 2018.

[2] Margaret H. Pinson, “The Consumer Digital Video Library [Best of the Web],” IEEE Signal Processing Magazine, vol. 30, no. 4, pp. 172,174, July 2013 doi: 10.1109/MSP.2013.2258265


High Frame Rate Video

As the demand for higher quality and more immersive video content increases, the need to extend the current video parameter space of spatial resolutions and display sizes, to include, among other things, a wider colour gamut, higher dynamic range and higher frame rates, becomes ever greater. The use of increased frame rate can provide a more realistic portrayal of a scene through a reduction in motion blur, while also minimizing temporal aliasing, and the associated visual artefacts.

The BVI-HFR video database is the first publicly available high frame rate video database, and contains 22 unique HD video sequences at frame rates up to 120 Hz. Sample frames from some of the video sequences can be seen below:

sparkler hamster catch flowers bobblehead cyclist










Subjective evaluations of 51 participants on the sequences in the BVI-HFR video database have shown a clear relationship between frame rate and perceived quality (MOS), although we do see the effect of diminishing returns. The results also showed that a degree of content dependency exists, for example benefits of higher frame rate material are more likely to be observed in video sequences with high motion speed (i.e. moving camera).




A STUDY OF SUBJECTIVE VIDEO QUALITY AT VARIOUS FRAME RATES, Mackin, A. and Zhang, F. and Bull, D., Image Processing (ICIP), 2015 22nd IEEE International Conference on, 2015.































































What’s on TV: A Large-Scale Quantitative Characterisation of Modern Broadcast Video Content

Video databases, used for benchmarking and evaluating the performance of new video technologies, should represent the full breadth of consumer video content. The parameterisation of video databases using low-level features has proven to be an effective way of quantifying the diversity within a database. However, without a comprehensive understanding of the importance and relative frequency and of these features in the content people actually consume, the utility of such information is limited. In collaboration with the BBC, the  “What’s on TV” is a large-scale analysis of the low-level features that exist in contemporary broadcast video. The project aims to establish an efficient set of features that can be used to characterise the spatial and temporal variation in modern consumer content. The meaning and relative significance of this feature set, together with the shape of their frequency distributions, represent highly valuable information for researchers wanting to model the diversity of modern consumer content in representative video databases.


Felix Mercer Moss, Fan Zhang, Roland Baddeley and David Bull, What’s on TV: A large-scale quantitative characterisation of modern broadcast video content, ICIP 2016.


Adaptive Resolution Intra Coding

Delivering high resolution video in restricted bandwidth scenarios can be challenging.  Part of the reason for this is the high bitrate requirement of the intra-coded Instantaneous Decoding Refresh (IDR) pictures featuring in all video coding standards. Frequent coding of IDR frames is essential for error resilience in order to prevent the occurrence of error propagation. However, as each one consumes a huge portion of the available bitrate, the quality of future coded frames is hindered by high levels of compression. This work looks at new adaptive resolution intra coding methods for improving the rate distortion performance of the video codec.


B. Hosking, D. Agrafiotis, and D. Bull, “Spatial resampling of IDR frames for low bitrate video coding with HEVC,” IS&T/SPIE Electronic Imaging, San Francisco, Feb 2015.

B. Hosking, D. Agrafiotis, D. Bull, and N. Easton, “AN ADAPTIVE RESOLUTION RATE CONTROL METHOD FOR INTRA CODING IN HEVC,” IEEE International Conference on Acoustics, Speech and Signal Processing, Shanghai, March 2016.




Effect of resampled coding of IDR frame to the quality of a reconstructed B frame in a Group of Pictures (similar bitrate): left resampled coded , middle original, right standard coded

Visual Attention Based Video Compression

Accurate prediction of the viewer’s gaze location in a video frame has the potential to improve bit allocation, rate control, error resilience and quality evaluation in video compression. With complex contexts, such as that of broadcast football video, the potential reward is even higher given that compression and transmission of this type of content is challenging. We have developed a gaze location (visual attention) prediction system for high definition broadcast football video. The system employs Bayesian integration of bottom-up features and context specific top-down cues. The context is classified into different categories through shot classification thus allowing our model to pre-learn the task pertinence of each object category and build the top-down prior map automatically.

Q. Cheng, D. Agrafiotis, A. M. Achim, D. R. Bull, “Gaze Location Prediction for Broadcast Football Video”, IEEE Transactions on Image Processing, vol 22, no. 12, pp. 4918-4929, 2013



Optimal presentation duration for video quality assessment

Video content distributors, codec developers and researchers in related fields often rely on subjective assessments to ensure that their video processing procedures result in satisfactory quality. The current 10-second recommendation for the length of test sequences in subjective video quality assessment studies, however, has recently been questioned. Not only do sequences of this length depart from modern cinematic shooting styles, the use of shorter sequences would enable substantial efficiency improvements to the data collection process. This project, therefore, aims to explore the impact upon viewer rating behaviour of using different length video sequences and the consequent savings that could be made in time, labour and money .



Felix Mercer Moss, Ke Wang, Fan Zhang, Roland Baddeley and David R. Bull, On the optimal presentation duration for subjective video quality assessment, IEEE Transactions on Circuits and Systems for Video Technology, Volume PP, Issue 99, July 2015.

Felix Mercer Moss, Chun-Ting Yeh, Fan Zhang, Roland Baddeley and David R. Bull, Support for reduced presentation durations in subjective video quality assessment, Signal Processing: Image Communication, Volume 48, October 2016, Pages 38-49.