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VMQ: an algorithm for measuring the Video Motion Quality Nawaf O. Alsrehin; Ahmad F. Klaib
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (541.692 KB) | DOI: 10.11591/eei.v8i1.1418

Abstract

This paper proposes a new full-reference algorithm, called Video Motion Quality (VMQ) that evaluates the relative motion quality of the distorted video generated from the reference video based on all the frames from both videos. VMQ uses any frame-based metric to compare frames from the original and distorted videos. It uses the time stamp for each frame to measure the intersection values. VMQ combines the comparison values with the intersection values in an aggregation function to produce the final result. To explore the efficiency of the VMQ, we used a set of raw, uncompressed videos to generate a new set of encoded videos. These encoded videos are then used to generate a new set of distorted videos which have the same video bit rate and frame size but with reduced frame rate. To evaluate the VMQ, we applied the VMQ by comparing the encoded videos with the distorted videos and recorded the results. The initial evaluation results showed compatible trends with most of subjective evaluation results.
VMQ: an algorithm for measuring the Video Motion Quality Nawaf O. Alsrehin; Ahmad F. Klaib
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (545.187 KB) | DOI: 10.11591/eei.v8i2.1418

Abstract

This paper proposes a new full-reference algorithm, called Video Motion Quality (VMQ) that evaluates the relative motion quality of the distorted video generated from the reference video based on all the frames from both videos. VMQ uses any frame-based metric to compare frames from the original and distorted videos. It uses the time stamp for each frame to measure the intersection values. VMQ combines the comparison values with the intersection values in an aggregation function to produce the final result. To explore the efficiency of the VMQ, we used a set of raw, uncompressed videos to generate a new set of encoded videos. These encoded videos are then used to generate a new set of distorted videos which have the same video bit rate and frame size but with reduced frame rate. To evaluate the VMQ, we applied the VMQ by comparing the encoded videos with the distorted videos and recorded the results. The initial evaluation results showed compatible trends with most of subjective evaluation results.
VMQ: an algorithm for measuring the Video Motion Quality Nawaf O. Alsrehin; Ahmad F. Klaib
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (545.187 KB) | DOI: 10.11591/eei.v8i2.1418

Abstract

This paper proposes a new full-reference algorithm, called Video Motion Quality (VMQ) that evaluates the relative motion quality of the distorted video generated from the reference video based on all the frames from both videos. VMQ uses any frame-based metric to compare frames from the original and distorted videos. It uses the time stamp for each frame to measure the intersection values. VMQ combines the comparison values with the intersection values in an aggregation function to produce the final result. To explore the efficiency of the VMQ, we used a set of raw, uncompressed videos to generate a new set of encoded videos. These encoded videos are then used to generate a new set of distorted videos which have the same video bit rate and frame size but with reduced frame rate. To evaluate the VMQ, we applied the VMQ by comparing the encoded videos with the distorted videos and recorded the results. The initial evaluation results showed compatible trends with most of subjective evaluation results.