Between the Frames - Evaluation of Various Motion Interpolation Algorithms to Improve 360° Video Quality

With the increasing availability of 360° video content, it becomes important to provide smoothly playing videos of<br> high quality for end users. For this reason, we compare the influence of different Motion Interpolation (MI) algorithms on 360°<br> video quality. After conducting a pre-test with 12 video experts in [3], we found that MI is a useful tool to increase the QoE (Quality<br> of Experience) of omnidirectional videos. As a result of the pretest, we selected three suitable MI algorithms, namely ffmpeg<br> Motion Compensated Interpolation (MCI), Butterflow and Super- SloMo. Subsequently, we interpolated 15 entertaining and realworld<br> omnidirectional videos with a duration of 20 seconds from 30 fps (original framerate) to 90 fps, which is the native refresh<br> rate of the HMD used, the HTC Vive Pro. To assess QoE, we conducted two subjective tests with 24 and 27 participants. In<br> the first test we used a Modified Paired Comparison (M-PC) method, and in the second test the Absolute Category Rating<br> (ACR) approach. In the M-PC test, 45 stimuli were used and in the ACR test 60. Results show that for most of the 360° videos, the<br> interpolated versions obtained significantly higher quality scores than the lower-framerate source videos, validating our hypothesis<br> that motion interpolation can improve the overall video quality for 360° video. As expected, it was observed that the relative<br> comparisons in the M-PC test result in larger differences in terms of quality. Generally, the ACR method lead to similar results,<br> while reflecting a more realistic viewing situation. In addition, we compared the different MI algorithms and can conclude that<br> with sufficient available computing power Super-SloMo should be preferred for interpolation of omnidirectional videos, while<br> MCI also shows a good performance.