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Using Artificial Neural Network for Automatic Assessment of Video Sequences

Auteur(s) : B. Ekobo Akoa, E. Simeu, F. Lebowsky

Doc. Source: 27th International Conference on Advanced Information Networking and Applications Workshops (WAINA'13)

Publisher : IEEE

Pages : 285-290

Doi : 10.1109/WAINA.2013.191

This paper presents a methodology for monitoring quality of service in multimedia networks. The proposal consists in the use of a simple and generic artificial neural networks (ANN) architecture that enables predicting the video quality. The main purpose is to develop automatic means for generating a numerical score that quantifies objectively the human assessing of video streams. The challenge is to create a video quality measurement tool (VQMT) assessing the video quality directly from the available measurements, by building a nonlinear correlation map between the measurements and the human rating mean opinion score (MOS). Promising results are obtained using the ANN for nonlinear modeling combined with fundamental measurable metrics, namely packet loss rate, peak signal to noise ratio, spatial indexes and temporal indexes. A statistical analysis is provided comparing this solution's performance with data-sets obtained through subjective human rating.