%0 Journal Article %1 IJACSA.2012.030601 %A Xinchen Zhang Lihau Wu, Yuan Fang Hao Jiang %D 2012 %J International Journal of Advanced Computer Science and Applications(IJACSA) %K (VQA); BP assessment full network. neural objective performance; quailty reference; score; subjective video %N 6 %T A Study of FR Video Quality Assessment of Real Time Video Stream %U http://ijacsa.thesai.org/ %V 3 %X To assess the real-time transmission video’s quality, this paper persents a approach which used FR video quality assessment (VQA) model to satisfy the objective and subjective measurement requirement. If we want to get the reference video in the measuring terminal and to make a assessment, there are two problems which are how to certain the reference video frame and how to make the objective score close to the subject assessment. We present in this paper a novel method of computing the order number of the video frame in the test point. In order to establish the relationship between the objective distortion and the subjective score, we used the “best-fit” regressed curve model and the BP neural network to describe prediction formula. This work is the mainly aim to get the high accurency assessment results with the human subjective feeling. So we select huge video sources for testing and training. The experimental results show that the proposed approach is suit to assess the video quality using FR model and the converted subjective score is available.

@article{IJACSA.2012.030601, abstract = {To assess the real-time transmission video’s quality, this paper persents a approach which used FR video quality assessment (VQA) model to satisfy the objective and subjective measurement requirement. If we want to get the reference video in the measuring terminal and to make a assessment, there are two problems which are how to certain the reference video frame and how to make the objective score close to the subject assessment. We present in this paper a novel method of computing the order number of the video frame in the test point. In order to establish the relationship between the objective distortion and the subjective score, we used the “best-fit” regressed curve model and the BP neural network to describe prediction formula. This work is the mainly aim to get the high accurency assessment results with the human subjective feeling. So we select huge video sources for testing and training. The experimental results show that the proposed approach is suit to assess the video quality using FR model and the converted subjective score is available.}, added-at = {2014-02-21T08:00:08.000+0100}, author = {{Xinchen Zhang Lihau Wu}, Yuan Fang Hao Jiang}, biburl = {https://www.bibsonomy.org/bibtex/235d15cc3f89fe8bd12d9a7b568d5f480/thesaiorg}, interhash = {b3ae064c10f7937386d62395d9cadd25}, intrahash = {35d15cc3f89fe8bd12d9a7b568d5f480}, journal = {International Journal of Advanced Computer Science and Applications(IJACSA)}, keywords = {(VQA); BP assessment full network. neural objective performance; quailty reference; score; subjective video}, number = 6, timestamp = {2014-02-21T08:00:08.000+0100}, title = {{A Study of FR Video Quality Assessment of Real Time Video Stream}}, url = {http://ijacsa.thesai.org/}, volume = 3, year = 2012 }