No-Reference Model for Video Quality Assessment Based on SVM

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. 1-15 ◽  
Author(s):  
Jiarun Song ◽  
Fuzheng Yang

Packet loss will make severe errors due to the corruption of related video data. For most video streams, because the predictive coding structures are employed, the transmission errors in one frame will not only cause decoding failure of itself at the receiver side, but also propagate to its subsequent frames along the motion prediction path, which will bring a significant degradation of end-to-end video quality. To quantify the effects of packet loss on video quality, a no-reference objective quality assessment model is presented in this paper. Considering the fact that the degradation of video quality significantly relies on the video content, the temporal complexity is estimated to reflect the varying characteristic of video content, using the macroblocks with different motion activities in each frame. Then, the quality of the frame affected by the reference frame loss, by error propagation, or by both of them is evaluated, respectively. Utilizing a two-level temporal pooling scheme, the video quality is finally obtained. Extensive experimental results show that the video quality estimated by the proposed method matches well with the subjective quality.


2014 ◽  
Vol 60 (3) ◽  
pp. 436-444 ◽  
Author(s):  
Demóstenes Z. Rodríguez ◽  
Renata L. Rosa ◽  
Eduardo A. Costa ◽  
Julia Abrahão ◽  
Graca Bressan

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