A Reduced Reference Metric for Enhanced 3D Video Perception

Currently, one of the trending research topics among the researchers assisting to the enhancement of the 3D video services relies on the 3 Dimensional (3D) video Quality of Experience (QoE) prediction metric development process. The researches for this trending topic can be ensured by characterizing the 3D video related features in the most compatible way as possible in this process. Considering this fact, a novel Reduced Reference (RR)) 3D video QoE prediction metric relying on color+depth map 3D video representation is developed in this study. The developed metric utilizes the incorporation of  the Significant Information (SI) in the depth map videos with the Structual Complexity Information (SCI) of their color counterparts. The abstraction filter and Structural SIMilarity Index (SSIM) are exploited for the SI and SCI computations, respectively. Performed subjective experment results are utilized to predict the performance of the developed metric. Observing highly effective results after the performance evaluation process, it can be clearly stated that the developed RR metric is compatible for assisting the advancement of the 3D video services.

A Reduced Reference Metric for Enhanced 3D Video Perception

Currently, one of the trending research topics among the researchers assisting to the enhancement of the 3D video services relies on the 3 Dimensional (3D) video Quality of Experience (QoE) prediction metric development process. The researches for this trending topic can be ensured by characterizing the 3D video related features in the most compatible way as possible in this process. Considering this fact, a novel Reduced Reference (RR)) 3D video QoE prediction metric relying on color+depth map 3D video representation is developed in this study. The developed metric utilizes the incorporation of  the Significant Information (SI) in the depth map videos with the Structual Complexity Information (SCI) of their color counterparts. The abstraction filter and Structural SIMilarity Index (SSIM) are exploited for the SI and SCI computations, respectively. Performed subjective experment results are utilized to predict the performance of the developed metric. Observing highly effective results after the performance evaluation process, it can be clearly stated that the developed RR metric is compatible for assisting the advancement of the 3D video services.

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