Due to the growing importance of optimizing quality and efficiency of video streaming delivery, accurate assessment of user perceived video quality becomes increasingly relevant. However, due to the wide range of viewing distances encountered in real-world viewing settings, actually perceived video quality can vary significantly in everyday viewing situations. In this paper, we investigate and quantify the influence of viewing distance on perceived video quality. A subjective experiment was conducted with full HD sequences at three different stationary viewing distances, with each video sequence being encoded at three different quality levels. Our study results confirm that the viewing distance has a significant influence on the quality assessment. In particular, they show that an increased viewing distance generally leads to an increased perceived video quality, especially at low media encoding quality levels. In this context, we also provide an estimation of potential bitrate savings that knowledge of actual viewing distance would enable in practice. Since current objective video quality metrics do not systematically take into account viewing distance, we also analyze and quantify the influence of viewing distance on the correlation between objective and subjective metrics. Our results confirm the need for distance-aware objective metrics when accurate prediction of perceived video quality in real-world environments is required.

1. On the Impact of Viewing Distance on Perceived Video Quality
Hadi Amirpour 1
Raimund Schatz 2
Christian Timmerer 1
Mohammad Ghanbari 1,3
1
Christian Doppler Laboratory ATHENA, Alpen-Adria-Universität, Klagenfurt, Austria
2
AIT Austrian Institute of Technology, Austria 3
School of Computer Science and Electronic Engineering, University of Essex, UK
Paper ID: 093
VCIP 2021
Introduction
Due to the growing importance of optimizing the quality and efficiency of video streaming
delivery, accurate assessment of user-perceived video quality becomes increasingly impor-
tant.
Due to the wide range of viewing distances encountered in real-world viewing settings, the
perceived video quality can vary significantly in everyday viewing situations.
Figure 1. There is a wide range of viewing distances in real-world viewing settings.
Although some studies in this direction already exist, their focus mainlywas on (low resolution)
images rather than on video sequences.
We argue that in the context of video quality the relation between the viewing distance and
the perceived quality should be more systematically investigated.
In this paper, we empirically study the impact of viewing distance on perceived video quality.
Additionally, the impact of viewing distance on the correlation between common objective
metrics and subjective scores is investigated to answer the following two research questions:
RQ1: How does varying the viewing distance influence subjective video quality ratings?
RQ2: How does changing the viewing distance alter the correlation between the estimated
objective video quality metrics and subjective ground truth data?
Subjective Experiment Design
Test Content
Based on SI and TI, video sequences were grouped into five clusters using k-means clustering.
In total, 10 sequences (two from each cluster) have been selected for the subjective test.
All sequences were 8-bit, 1080p in resolution, and had 5 or 10 seconds duration.
x265 (version 3.4) was used to encode video sequences at three quality/distortion levels,
namely excellent (imperceptible), good (perceptible, but not annoying), and fair quality (slightly
annoying) determined by an expert review.
Test Environment
Our laboratory was set up according to ITU BT.500-13.
We used a Samsung LE46C750R2Z 46” Full HD TV as display, color calibrated, and with all
image enhancements turned off.
We calculated the (closest) optimal viewing distance using the following equation:
V D =
DS
q
(NHR
NV R)2 + 1 × CV R × tan( 1
60)
(1)
where DS is display size, and NHR and NVR are the display’s native horizontal and vertical
resolutions, respectively. CVR represents the vertical resolution of the video.
For our experimental setup, the optimal viewing distance d1 was equal to 3.2H = 1.82m, with
H being the height of the display.
We added two non-optimal, larger viewing distances d2, d3 to our test design, resulting in the
following three distance levels:
d1= 1.82m (3.2H), d2= 2.80m (4.9H), d3= 3.90m (6.85H)
The latter two additional distances were chosen because they represent more common view-
ing distances used in practice.
Test Protocol
Absolute Category Rating (ACR) was selected as testing method.
Participants rated the overall perceived quality of the video sequences using a 7-point Likert
scale. Each subject scored 90 stimuli in total, which took 23 minutes per subject on average.
In total, 25 subjects (avg. age 28; 14 male and 11 female) participated in the subjective test.
Video sequences and the order of distances were randomly selected for each subject.
Evaluation Results
The impact of the viewing distance on the perceived video quality (MOS) at different encoding
quality levels per each clip (RQ1) is shown in Fig. 2.
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Figure 2. MOS as function of viewing distance for the three encoding quality levels (coloured) per clip (CI = 95%). q1 and q3 are the
lowest and highest quality levels, respectively.
For a better understanding, MOS values per each quality are aggregated and they are shown in
Fig. 3. Additionally, the averaged Differential Mean Opinion Scores (DMOS) against the closest
distance (d1) for each quality level are summarized in Table 1.
Fig. 4a plots the MOS against the three quality levels for Clip 4 (CrowdRun) as an example.
Fig. 4 (b-d) shows scatter plots forVMAF, SSIM, and PSNR including quadratic regression curves
by clip, distance, and quality. Fig. 4c shows how increased viewing distance alters the correla-
tion between subjective and objective scores by making it not only weaker but also less linear.
d1 d2 d3 d1 d2 d3 d1 d2 d3
1
2
3
4
5
6
MOS
q1 q2 q3
Figure 3. DMOS values for the middle distance (d2) and further distance
(d3) against the closest distance (d1) for each quality level.
Table 1. MOS as function of viewing distance for each
encoding quality level (CI = 95%).
q1 q2 q3
d2 0.52 0.54 0.02
d3 1.18 0.83 0.04
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Figure 4. (a) MOS against quality (bitrate) for Clip 4 (CrowdRun) considering three distances. Scatter plots and quadratic regression
curves for (b) VMAF, (c) SSIM, and (d) PSNR scores against MOS ground truths for the three distance levels.
The correlation between objective and subjective metrics as well as video bitrate, SI, and TI are shown in Fig. 5
that illustrates how increasing viewing distances weaken the correlation between objective and subjective re-
sults.
The impact of distance on the correlation between subjective and objective metrics becomes even more salient
when plotting normalized PCC values against distance as depicted in Fig. 6.
We also performed an ANOVA test to validate our results and summarized F and ρ values in Table 2.
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Figure 5. Pearson correlation heatmap for
MOS (at different distances) as well as different
objective metrics and technical parameters.
Figure 6. Normalized Pearson correlation with sub-
jective ratings for different objective quality metrics
as function of distance (PCC at d1= 100%).
Table 2. ANOVA summary
statistics per video quality level.
q1 q2 q3
F 50.54 38.69 0.13
ρ 0.0001 0.0001 0.87
Acknowledgment
The financial support of the Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for
Research, Technology, and Development, and the Christian Doppler Research Association is gratefully acknowl-
edged. Christian Doppler Laboratory ATHENA: https://athena.itec.aau.at/.
https:/
/www.athena.itec.aau.at IEEE International Conference on Visual Communications and Image Processing 2021 (VCIP2021) hadi.amirpour@aau.at