Exposure of 3D-Stereoscopic Videos Defects using Binocular Disparity

Abstract

3D video quality issues that may bother the human visual systemand adversely affect the 3D seeing knowledge are notable and turn out to be more applicable as the accessibility of 3D video content increments, fundamentally via 3D silver screen, yet additionally via 3D TV. In this paper, we introduce four algorithms that adventure accessible stereo uniqueness data, keeping in mind the end goal to distinguish aggravating stereoscopic impacts, specifically Stereoscopic Window Violations (SWV), bowed window impacts, UFO items and profundity bounce cuts on stereo videos. In the wake of distinguishing such effects, the introduced algorithms describe them, in light of the pressure they cause to the watcher's visual framework. Subjective agent illustrations, quantitative test comes about on a uniquely crafted video dataset, a parameter variation study and remarks on the calculated multifaceted nature of the algorithms are given, with a specific end goal to survey the precision and execution of stereoscopic quality deformity discovery.