Abstract
The level of visual comfort human perceive for stereoscopic three-dimensional (S3D) images has been taking an important role in recent decades. Generally, the subjective assessment has been used to evaluate the visual comfort. However, it is time-consuming and man-powered experimental process. So how to develop effective and faithful objective visual comfort assessment (VCA) model is still a challenge. In the paper, we have proposed a new approach for objective evaluation based on the back propagation(BP) neural network. To establish the assessment model, the content and disparities related features of visual important regions (VIR) were both considered as the input. Experimental results showed high consistency with subject judgment compared with the state-of-the-art models on the same benchmark database.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
