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The raise of 3D image market is rapid. In previous work [Wang
2008], distortion and grid line bending constraints is adapted to
image resizing while important areas remain the same scale. In
another previous work [Lang 2010], disparity of input stereo
image is remapped, and warped stereo image pairs are
manipulated by similar constraints. In our system, we adapt image
constraints similar to Lang’s work, but for a depth refinement
purpose. Original random and sharp depth error causes
deformation and large defect of hole-filling. These errors are
refined, but with a consequence of blurred depth edge. So we
adapt another circuit model constraint to sharpen the depth edge
again, but maintain the smoothed results at the same time. This
technique is modified from previous work [Grady 2006], pixels
are electrical circuit nodes with resistance derived from RGB
difference. Generally, temporal smooth in video processing needs
information from several frames. But in our system, no multiple
frames involve but only current frame. In the same scene,
different frames share similar color and shape. Since depth map is
refined by 2D image, and temporal 2D images are similar, refined
depths tend to be smoothed and sharpened in similar way. Finally,
depth map of previous frame is used as an initial depth map of
current optimization. Experiment results in Figure 1 & 2 show
significant improvement. |
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