Video quality assessment in video streaming services considering user preference for video content

2014 ◽  
Vol 60 (3) ◽  
pp. 436-444 ◽  
Author(s):  
Demóstenes Z. Rodríguez ◽  
Renata L. Rosa ◽  
Eduardo A. Costa ◽  
Julia Abrahão ◽  
Graca Bressan
2013 ◽  
Vol 846-847 ◽  
pp. 1024-1030
Author(s):  
Li Li Wu ◽  
Chun Yan Yu

This paper focuses on the video distortion which is caused by the packet loss. Considering the relationship between the human visual perception which is caused by the packet loss and the visual characteristic of the video content, we present a no-reference model for video quality assessment based on Support Vector Machine. The feature vector of the SVM contain temporal complexity, spatial complexity, the average number of bits per frame and the packet loss rate. Temporal complexity, spatial complexity and the average number of bits per frame represent the visual characteristic of the video content. The value of the packet loss rate means the distortion which is caused by the packet loss intuitively. Experimental results show that this model has a good consistency with the subjective.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Milan Mirkovic ◽  
Petar Vrgovic ◽  
Dubravko Culibrk ◽  
Darko Stefanovic ◽  
Andras Anderla

Video quality as perceived by human observers is the ground truth when Video Quality Assessment (VQA) is in question. It is dependent on many variables, one of them being the content of the video that is being evaluated. Despite the evidence that content has an impact on the quality score the sequence receives from human evaluators, currently available VQA databases mostly comprise of sequences which fail to take this into account. In this paper, we aim to identify and analyze differences between human cognitive, affective, and conative responses to a set of videos commonly used for VQA and a set of videos specifically chosen to include video content which might affect the judgment of evaluators when perceived video quality is in question. Our findings indicate that considerable differences exist between the two sets on selected factors, which leads us to conclude that videos starring a different type of content than the currently employed ones might be more appropriate for VQA.


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