Yijian Xiang

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We propose an analytical model to estimate the depth-error-induced virtual view synthesis distortion (VVSD) in 3D video, taking into account the configuration of the cameras. Focusing on view synthesis under depth error, we carefully analyze the merging operations under different situations that affect pixel availability: overlapping region, disocclusion(More)
We propose an analytical model to estimate the depth-error-induced virtual view synthesis distortion (VVSD) in 3D video, taking the distance between reference and virtual views (virtual view position) into account. In particular, we start with a comprehensive preanalysis and discussion over several possible VVSD scenarios. Taking intrinsic characteristic of(More)
We propose an analytical model to estimate the depth-error-induced synthesis distortion in 3D video, taking into account the configuration of the cameras. In particular, the model mathematically relates the Distance between camera positions (reference view and virtual view) to the Virtual View Distortion (VVD), thus it is denoted as DVVD model.(More)
In this paper, we provide a novel regression algorithm based on a Gaussian random field (GRF) indexed by a Riemannian manifold (M, g). We utilize both the labeled and unlabeled data sets to exploit the geometric structure of M. We use the recovered heat (H) kernel as the covariance function for the GRF (HGRF). We propose a Monte Carlo integral theorem on(More)
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