The current renaissance of 3D movies has drawn more and more attention from the audience. Three-dimensional
television (3DTV) has been expected to be the next advance in television. Studies have shown that different people have
different comfort range of depth in a 3D content, especially in 3DTV scenario, wherein much smaller screen sizes and
viewing distances in home setup than in theater put more restrictions on the 3D content fed into the 3DTV. As a result,
the version of the 3D content sent to home will not satisfy all the people in one family. In this paper, we try to solve this
problem by providing a prediction of viewing discomfort of certain input content by certain viewer. Our method is based
on the Disparity Discomfort Profile (DDP) built through subjective test for each viewer. The input content is analyzed by
studying its disparity distribution. The prediction of discomfort is performed by matching the disparity distribution with
the viewer's DDP. Then a mechanism to allow the viewers to adjust the depth range according to their visual comfort
profile or viewing preference is used to minimize the discomfort. Experiments show promising results of the proposed
Digital fingerprinting is an emerging technology to protect multimedia from unauthorized use by embedding a unique fingerprint signal into each user's copy. A robust embedding algorithm is an important building block in order to make the fingerprint resilient to various distortions and collusion attacks. Spread spectrum embedding has been widely used for multimedia fingerprinting. In this paper, we explore another class of embedding methods - Quantization Index Modulation (QIM) for fingerprinting applications. We first employ Dither Modulation (DM) technique and extend it for embedding multiple symbols through a basic dither sequence design. We then develop a theoretical model and propose a new algorithm to improve the collusion resistance of the basic scheme. Simulation results show that the improvement algorithm enhances the collusion resistance, while there is still a performance gap with the existing spread spectrum based fingerprinting. We then explore coded fingerprinting based on spread transform dither modulation (STDM) embedding. Simulation results show that this coded STDM based fingerprinting has significant advantages over spread spectrum based fingerprinting under blind detection.
This paper proposes a group-based fingerprinting scheme employing
a joint coding and embedding strategy to trace multimedia distribution and proactively prevent the leak of multimedia information. Taking advantage of the prior knowledge on the collusion pattern, we construct compact fingerprints that consist
of user sub-codeword and group sub-codeword and are embedded in host signal via spread spectrum technique. The detection is done in two levels, which identifies guilty groups through correlation and then narrows down to specific colluders through minimum distance decoding. Experimental results show that the proposed method provides higher collusion resistance than the existing non-grouped fingerprint codes.