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Recently, 2D-to-3D video conversion has raised great interest because of the increasing demand of 3D video contents. A critical component in semi-automatic methods is to estimate the depth information of non-key frames from key frames. To overcome the sensitiveness to occlusion in existing schemes, a depth propagation method is proposed in this paper where tensor voting is leveraged to eliminate occlusion...
2D to 3D video conversion has become a popular manner to produce 3D contents, in which the key task is to estimate the depth for the images. However, the main limitation of conventional motion-based depth propagation methods is that they are susceptible to inaccurate motion estimation and occlusion. To address this problem, we propose a two-stage structure-aware depth propagation method for semi-automatic...
Summary form only given. In this paper, we propose an optimized in painting-based macro block(MB) prediction mode (IP-mode) in the state-of-the-art H.264/AVC video compression engine, and belief propagation (BP) is applied to achieve the global spatio-temporal consistency between the predicted content and the co-located known region. To decrease the computing complexity of the iterative BP algorithm,...
This paper presents a new video compression framework over H.264/AVC scheme that integrates our proposed structured priority belief propagation (BP)-based inpainting prediction (IP) to exploit the intrinsic nonlocal and geometric regularity in video samples. Unlike the existing edge-based inpainting adopted in lossy image coding, the optimal predictor could maintain the pixel-wise fidelity and the...
In this paper, we propose an optimized inpainting-based macroblock (MB) prediction mode (IP-mode) in the state-of-the-art H.264/AVC video compression engine, and investigate a natural extension of structured sparsity over the ordered Belief Propagation (BP) inference in inpainting-based prediction. The IP-mode is regularized by a global spatio-temporal consistency between the predicted content and...
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