Subjective quality estimation based on neural networks for stereoscopic videos

A neural network based technique is proposed to estimate subjective quality of stereoscopic videos. Moreover, to utilize this model for applications where availability of reference signal is not possible to receiver, it applies objective quality of video with minimum dependency on reference signal. This paper presents fast, accurate and consistent subjective quality estimation. Feasibility and accuracy of the proposed technique is thoroughly analyzed with extensive subjective experiments and simulations. Results illustrate that performance measure of 92.3% in subjective quality estimation can be achieved with the proposed technique.