Subjective quality evaluation of video sequences by using motion information

Caramma, M.; Lancini, R.; Marconi, M. C.

doi:10.1109/icip.1999.822907

Cited by 8 publications

(3 citation statements)

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“…In [9], the analysis goes deeper: the authors present a study of the effect of motion on the perceived video quality. In [23], a dynamic bit-rate prediction method is proposed.…”

Section: Related Workmentioning

confidence: 99%

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A study of real-time packet video quality using random neural networks

Mohamed

Rubino

2002

IEEE Trans. Circuits Syst. Video Technol.

212

130

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An important and unsolved problem today is that of automatic quantification of the quality of video flows transmitted over packet networks. In particular, the ability to perform this task in real time (typically for streams sent themselves in real time) is especially interesting. The problem is still unsolved because there are many parameters affecting video quality, and their combined effect is not well identified and understood. Among these parameters, we have the source bit rate, the encoded frame type, the frame rate at the source, the packet loss rate in the network, etc. Only subjective evaluations give good results but, by definition, they are not automatic. We have previously explored the possibility of using artificial neural networks (NNs) to automatically quantify the quality of video flows and we showed that they can give results well correlated with human perception. In this paper, our goal is twofold. First, we report on a significant enhancement of our method by means of a new neural approach, the random NN model, and its learning algorithm, both of which offer better performances for our application. Second, we follow our approach to study and analyze the behavior of video quality for wide range variations of a set of selected parameters. This may help in developing control mechanisms in order to deliver the best possible video quality given the current network situation, and in better understanding of QoS aspects in multimedia engineering.Index Terms-Packet video, random neural networks, real-time video transmission, video quality assessment, video signal characterization.

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“…In [9], the analysis goes deeper: the authors present a study of the effect of motion on the perceived video quality. In [23], a dynamic bit-rate prediction method is proposed.…”

Section: Related Workmentioning

confidence: 99%

“…Subjective quality-assessment methods [9], [5], [2], [10], [3] measure the overall perceived video quality. They are carried out by human subjects.…”

Section: Introductionmentioning

confidence: 99%

A study of real-time packet video quality using random neural networks

Mohamed

Rubino

2002

IEEE Trans. Circuits Syst. Video Technol.

212

130

View full text Add to dashboard Cite

show abstract

“…In [37] the assumption is made, that quality degradation in MPEG-2 is correlated to the accuracy of motion vector estimation. Specifically, the authors state that motion estimation is highly related to the mean absolute error (MAE), computed by subtracting each pel in a block with its corresponding motion compensated reference block, and to spatial activity (SA), as the amount of texture in a macro-block.…”

Section: A Single Feature Metricsmentioning

confidence: 99%