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Audiovisual Technology Group

The Audiovisual Technology Group (AVT) deals with the function, application and perception of audio and video equipment. An essential focus of the research is on the relationship between the technical characteristics of audio, video and audiovisual systems and human perception and experience (“Quality of Experience”, QoE).

further information on the group


ITU-T standard for predicting video quality developed with the significant participation of the AVT department

ITU-T recently consented the P.1204 series of Recommendations titled “Video quality assessment of streaming services over reliable transport for resolutions up to 4K”. This work was jointly conducted by Question 14 of Study Group 12 (SG12/Q14) of the ITU-T and the Video Quality Experts Group (VQEG). Overall 9 companies and universities were part of this competition-based development, with the best set of models recommended as standards.

From the official ITU-T SG12 communication it reads:

"The P.1204 Recommendation series describes a set of objective video quality models. These can be used standalone for assessing video quality for 5-10 sec long video sequences, providing a 5-point ACR-type Mean Opinion Score (MOS) output. In addition, they deliver per-1-second MOS-scores that together with audio information and stalling / initial loading data can be used to form a complete model to predict the impact of audio and video media encodings and observed IP network impairments on quality experienced by the end-user in multimedia streaming applications. The addressed streaming techniques comprise progressive download as well as adaptive streaming, for both mobile and fixed network streaming applications."

To date, the P.1204 series of Recommendations comprises four sub-recommendations, namely P.1204 (an introductory document for the whole P.1204 series), P.1204.3 (bitstream-based model with full access to bitstream), P1204.4 (reference-/pixel-based model) and P1204.5 (hybrid bitstream- and pixel-based no-reference) with 2 more sub-recommendations, P1204.1 (meta-data-based) and P1204.2 (meta-data- and video-frame-information-based) planned to be consented by April 2020.

The AVT group of TU Ilmenau in collaboration with Deutsche Telekom were the sole winners in the category which resulted in Recommendation P1204.3 and are co-winners in the category which is planned to result in Recommendations P1204.1 and P1204.2 by April 2020.

In the official ITU-T SG12 communication it is further stated that: 

"The consent of the P.1204 model standards marks the first time that video-quality models of all relevant types have been developed and validated within the same standardization campaign. The respective “P.NATS Phase 2” model competition used a total of 13 video-quality test databases for training, and another 13 video-quality test databases for validation. With this comparatively high number of data (more than 5000 video sequences), the resulting standards deliver class-leading video-quality prediction performance."

The building blocks of the consented Recommendation


The project is a scientific cooperation between the labs of Audiovisual Technology, Virtual Worlds and Digital Games (Prof. Wolfgang Broll, Faculty of Economics and Media) and Electronic Media Technology (Prof. Karlheinz Brandenburg, Faculty of Electrical Engineering and Information Technology).

The project, funded by the Free State of Thuringia, was co-financed by the European Union within the European Regional Development Fund (ERDF).

Project Website

Offers for theses in the AVT Lab

Now you can inform yourself directly about the range of topics for bachelor and master theses as well as for media projects on our website .

Take a look under the point Theses!

Recent publications from the group

21st IEEE International Symposium on Multimedia (2019 IEEE ISM), Dec 9 - 11, 2019, San Diego, USA

Steve Göring, Christopher Krämmer, Alexander Raake

cencro – Speedup of Video Quality Calculation using Center Cropping

Today's video streaming providers, e.g. Youtube, Netflix or Amazon Prime, are able to deliver high resolution and high-quality content to end users. To optimize video quality and to reduce transmission bandwidth, new encoders and smarter encoding schemes are required. Encoding optimization forms an important part of this effort in reducing bandwidth and results in saving considerable amount of bitrate. For such optimization, accurate and computationally fast video quality models are required, e.g. Netflix's VMAF. However, VMAF is a full-reference (FR) metric, and the calculation of such metrics tend to be slower in comparison to other metrics, due to the amount of data that needs to be processed, especially for high resolutions of 4k and beyond.

We introduce an approach to speed up video quality metric calculations in general. We use VMAF as an example with a video database up to 4K resolution videos, to show that our approach works well.
Our main idea is that we reduce each frame of the reference and distorted video based on a center crop of the frame, assuming that most important visual information are presented in the middle of most typical videos. In total we analyze 18 different crop settings and compare our results with uncropped VMAF values and subjective scores. We show that this approach -- named cencro -- is able to save up to 95% computation time, with just an overall error of 4% considering a 360p center crop.

Furthermore, we checked other full-reference metrics, and show that cencro performs similar good. As a last evaluation, we apply our approach to full-hd gaming videos, also in this scenario cencro can be successfully applied.

The idea behind cencro is not restricted to full-reference models and can also be applied to other type of video quality models or datasets, or even for higher resolution videos such as 8K.

Link to the source code:

21st IEEE International Symposium on Multimedia (2019 IEEE ISM), Dec 9 - 11, 2019, San Diego, USA

Rakesh Rao Ramachandra Rao, Steve Göring, Werner Robitza, Bernhard Feiten, Alexander Raake

AVT-VQDB-UHD-1: A Large Scale Video Quality Database for UHD-1

4K television screens or even with higher resolutions are currently available in the market.Moreover video streaming providers are able to stream videos in 4K resolution and beyond.Therefore, it becomes increasingly important to have a proper understanding of video quality especially in case of 4K videos. To this effect, in this paper, we present a study of subjective and objective quality assessment of 4K ultra-high-definition videos of short duration, similar to DASH segment lengths.

As a first step, we conducted four subjective quality evaluation tests for compressed versions of the 4K videos. The videos were encoded using three different video codecs, namely H.264, HEVC, and VP9. The resolutions of the compressed videos ranged from 360p to 2160p with framerates varying from 15fps to 60fps. All the source 4K contents used were of 60fps. We included low-quality conditions in terms of bitrate, resolution and framerate to ensure that the tests cover a wide range of conditions, and that e.g. possible models trained on this data are more general and applicable to a wider range of real world applications. The results of the subjective quality evaluation are analyzed to assess the impact of different factors such as bitrate, resolution, framerate, and content.

In the second step, different state-of-the-art objective quality models were applied to all videos and their performance was analyzed in comparison with the subjective ratings, e.g. using Netflix's VMAF. The videos, subjective scores, both MOS and confidence interval per sequence and objective scores are made public for use by the community for further research.

Link to the videos:

21st IEEE International Workshop on Multimedia Signal Processing (MMSP), September 2019, Kuala Lumpur, Malaysia

A. Singla, W. Robitza and A. Raake

Comparison of Subjective Quality Test Methods for Omnidirectional Video Quality Evaluation

The test methods recommended by the International Telecommunication Union (ITU) for assessing 2D video quality are often used for evaluating omnidirectional / 360° videos. In this paper, we compare the performance of three different test methods, Absolute Category Rating (ACR), a modified version of ACR (M–ACR) with double presentation of the test stimulus, and DSIS (Double Stimulus Impairment Scale), based on the statistical reliability, assessment time and simulator sickness. Different settings were used for HEVC encoding of five 360° source videos of 10 s duration. Results indicate that DSIS is statistically more reliable with higher resolving power, followed by M–ACR and ACR. We found that simulator sickness increases with time, but can be reduced by taking breaks in between the test sessions. The results for simulator sickness are compared across test methods and with similar tests conducted under different contextual conditions. We also recorded and analyzed the exploration behaviour of the users. Apart from the methodological findings, the test results provide insights into video quality for different resolution and encoding settings (“bitrate ladders”). These may be useful for choosing appropriate representations in the context of HTTP-based adaptive streaming in case of full-frame streaming.

MOS with corresponding CIs for different test methods
The winners Domink Keller and Anton Schubert with the chairman of the Förderverein Prof. Seitz.

Prizes for Graduates of the AVT Group

For the second time, the Förderverein Elektrotechnik und Informationstechnik e. V. Ilmenau (Association for the Promotion of Electrical Engineering and Information Technology Ilmenau) in conjunction with the Department of Electrical Engineering and Information Technology of the TU Ilmenau presented its award for outstanding theses. The three endowed prizes honor the achievements of the students during the exmatriculation ceremony at the end of June. Fortunately, two master theses of the AVT group which were carried out with industrial partners were honored and awarded as outstanding due to their high degree of interdisciplinarity and scientific character as well as their execution.

We congratulate the award winners Anton Schubert, who has worked on the implementation of a compressed broadband audio codec for driver communication in motor sports, and Dominik Keller, who has worked on identification and analysis of texture dimensions in motion pictures using sensory evaluation techniques.

The youngest participant while watching Roller Coaster in VR during the event Lange Nacht der Technik 2019.

Best Paper Award

Dominik Keller (AVT Group), Tamara Seybold (ARRI Munich), Janto Skowronek (former AVT Group) and Alexander Raake (AVT Group) got the Best Paper Award at the 11th International Conference on Quality of Multimedia Experience (QoMEX 2019) in Berlin.

You find the abstract of the article below.

Dominik Keller, Tamara Seybold, Janto Skowronek, and Alexander Raake
Assessing Texture Dimensions and Video Quality in Motion Pictures using Sensory Evaluation Techniques

The paper resulting from the cooperation of members of the Audiovisual Technology Group and Scientific and Engineering Academy Award winner ARRI (Arnold & Richter Cine Technik) received Best Paper Award at this year’s 11th  Int. Conference on Quality of Multimedia Experience (QoMEX 2019).

The quality of images and videos is usually examined with well-established subjective tests or instrumental models. These often target content transmitted over the internet, such as streaming or videoconferences and address the human preferential experience. In the area of high-quality motion pictures, however, other factors are relevant. These mostly are not error-related but aimed at the creative image design, which has gained comparatively little attention in image and video quality research. To determine the perceptual dimensions underlying movie-type video quality, we combine sensory evaluation techniques extensively used in food assessment – Degree of Difference test and Free Choice Profiling – with more classical video quality tests. The main goal of this research is to analyze the suitability of sensory evaluation methods for high-quality video assessment. To understand which features in motion pictures are recognizable and critical to quality, we address the example of image texture properties, measuring human perception and preferences with a panel of image-quality experts. To this aim, different capture settings were simulated applying sharpening filters as well as digital and analog noise to exemplary source sequences. The evaluation, involving Multidimensional Scaling, Generalized Procrustes Analysis as well as Internal and External Preference Mapping, identified two separate perceptual dimensions. We conclude that Free Choice Profiling connected with a quality test offers the highest level of insight relative to the needed effort. The combination enables a quantitative quality measurement including an analysis of the underlying perceptual reasons.

External Preference Mapping results: Best ratings for stimuli of low noise and medium-high sharpness (Landscape scene)

Older News

Older news from the AVT lab can be found on this website.