A depth perception evaluation metric for immersive 3D video services


Nur Yılmaz G.

11th 3D True Vision v2: Research and Applications in Future 3D Media, 3DTV-CON 2017, Copenhagen, Denmark, 7 - 09 June 2017, vol.2017-June, pp.1-4 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 2017-June
  • Doi Number: 10.1109/3dtv.2017.8280420
  • City: Copenhagen
  • Country: Denmark
  • Page Numbers: pp.1-4
  • Keywords: 3D video, abstraction filter, depth perception, Reduced Reference (RR) metric, structural complexity, Structural SIMilarity metric (SSIM)
  • TED University Affiliated: No

Abstract

© 2017 IEEE.Burgeoning advances in 3 Dimensional (3D) video services provide a big leap on the proliferation of the investigations for developing reliable and competent perceptual 3D video Quality of Experience (QoE) metrics. This proliferation can only be supported by exploiting key features characterizing 3D video nature in these investigations. In this paper, a Reduced Reference (RR) metric is developed considering that the spatial resolution and perceptually significant depth level are two effective features for efficiently evaluating depth perception of the 3D video. In order to determine the perceptually significant depth levels in the depth map sequences, abstraction filter is exploited in the development of the proposed metric. Owing to the fact that the depth perception significantly differs for the depth map sequences having dissimilar relative depth levels, this feature is also incorporated with the proposed metric through normalized standard deviation. Structural SIMilarity metric (SSIM) is utilized to predict the depth perception degraded with the change in the perceptually important levels of the compressed depth maps having dissimilar spatial resolutions and relative depth levels. The performance assessment of the proposed RR metric proves the effectiveness of the proposed metric for ensuring immersive 3D video services.