Classification of Real 3D and Fake 3D Video. Issue 2 (4th March 2022)

• Record Type: Journal Article
• Authors: Rana, Shuvendu; Gaj, Sibaji; Sur, Arijit; Bora, Prabin Kumar
• Is Part Of: IETE journal of research. Volume 68:Issue 2(2022)
• Page Start: 947
• Page End: 956
• Publication Date: 2022-03-04
• Subjects: Depth-image-based rendering (DIBR) -- Fake 3D video -- LDA -- Parallax -- Real 3D video -- SIFT -- SVM -- 3DTV; Electronics -- Periodicals; Telecommunication -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/03772063.2019.1628667
• Languages: English
• ISSNs: 0377-2063

Abstract

Abstract : The tremendous growth in communication and media technology and the wide availability of cheaper end using devices have made 3D video communication very popular due to its immersive experience. It has been observed that a 3D video can be produced either by direct accusation using a 3D camera (say real 3D video) or by rendering from a set of 2D images (say fake 3D video). There are several occasions where it is required to distinguish between such real and fake 3D video sequences. In this paper, an algorithm is proposed which can distinguish the real 3D video from the fake one. A set of distinguishing features has been identified which are primarily based on the vertical parallax and sharpness peculiarities of object edges due to 3D acquisition process and rendering. Finally, two different supervised learning classifiers (Support Vector Machines and Linear discriminant analysis), are being trained using these features to detect the fake 3D video sequences. A comprehensive set of experiments has been carried out to justify the applicability of the proposed detection scheme over the recent existing scheme.