  Digital rights management (DRM) of depth-image-based rendering (DIBR) 3D
video is an emerging area of research. Existing schemes for DIBR 3D video cause
video distortions, are vulnerable to severe signal and geometric attacks,
cannot protect 2D frame and depth map independently or can hardly deal with
large-scale videos. To address these issues, a novel zero-watermark scheme
based on invariant feature and similarity-based retrieval for protecting DIBR
3D video (RZW-SR3D) is proposed in this study. In RZW-SR3D, invariant features
are extracted to generate master and ownership shares for providing
distortion-free, robust and discriminative copyright identification under
various attacks. Different from traditional zero-watermark schemes, features
and ownership shares are stored correlatively, and a similarity-based retrieval
phase is designed to provide effective solutions for large-scale videos. In
addition, flexible mechanisms based on attention-based fusion are designed to
protect 2D frame and depth map independently and simultaneously. Experimental
results demonstrate that RZW-SR3D have superior DRM performances than existing
schemes. First, RZW-SR3D can extracted the ownership shares relevant to a
particular 3D video precisely and reliably for effective copyright
identification of large-scale videos. Second, RZW-SR3D ensures lossless,
precise, reliable and flexible copyright identification for 2D frame and depth
map of 3D videos.
