Title :
A Simple Objective Method for Automatic Error Detection in Stereoscopic 3D Video
Author :
Shirish Sharma;Eva Cheng;Ian Burnett
Author_Institution :
Sch. of Electr. &
Abstract :
With the increased popularity of 3D videos online and through consumer and cinema media, there exist few techniques for the automatic detection of stereoscopic error in 3D videos. Further, techniques based on disparity estimation are imprecise and computationally complex. This paper proposes a simple objective method to detect common errors inherent to stereoscopic 3D content due to discrepant objects between the left and the right view of the image pairs, stereoscopic window violation and undesirably high binocular disparity that causes viewing discomfort. The technique proposed in this paper identifies stereoscopic errors by computing only the edge disparity, which is computationally less expensive and uses simplified methods that may be optimised for real-time computation. Evaluations of the proposed technique are conducted on a series of stereoscopic 3D videos containing common errors, where regions that contain a range of different errors are successfully and clearly identified.
Keywords :
"Three-dimensional displays","Stereo image processing","Streaming media","Quality assessment","Estimation","Image edge detection","Video recording"
Conference_Titel :
Big Data Visual Analytics (BDVA), 2015
DOI :
10.1109/BDVA.2015.7314285