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A simple objective method for automatic error detection in stereoscopic 3D video

conference contribution
posted on 2024-10-31, 19:45 authored by Shirish Sharma, Eva Cheng, Ian Burnett
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 pixel based 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.

History

Start page

1

End page

2

Total pages

2

Outlet

2015 Big Data Visual Analytics (BDVA)

Name of conference

2015 Big Data Visual Analytics (BDVA)

Publisher

IEEE

Place published

USA

Start date

2015-09-22

End date

2015-09-25

Language

English

Copyright

© 2015 IEEE

Former Identifier

2006063729

Esploro creation date

2020-06-22

Fedora creation date

2016-08-03

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