Nur Yilmaz, GokceBayrak, Huseyin2020-06-252020-06-252017closedAccess978-1-5090-6494-62165-0608https://hdl.handle.net/20.500.12587/710625th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEYDeveloping reliable and efficient 3 Dimensional (3D) video depth perception evaluation metrics is currently a trending research topic for supporting the advancement of the 3D video services. This support can be proliferated by utilizing effective 3D video features while modeling these metrics. In this study, a Reduced Reference (RR) depth perception evaluation metric using significant depth level and structural information as effective 3D video features is developed. The significant depth level and structural information in the Depth Maps (DM) are determined using abstraction filter and Canny edge detection algorithm, respectively. The performance assessment results of the proposed RR metric present that it is quite effective for ensuring advanced 3D video services.trinfo:eu-repo/semantics/closedAccess3D videoabstraction filterdepth perceptionReduced Reference (RR) metricstructural complexityConference Object2-s2.0-85026311856N/AWOS:000413813100585N/A