An Energy-Constrained Video Retargeting Approach for Color-Plus-Depth 3D Video


Color-plus-depth 3D video is booming up with the growing popularity of depth-sensing camera. This imposes new challenges on video resizing since the data embedded in the depth and color video ought to be considered simultaneously. In this paper, we propose an energy-constrained video retargeting approach for color-and-depth 3D video. We 1st build a 3D video visual attention (3DV-VA) computation model by combining gradient, saliency, motion and depth data. Then, an energy perform is generated using spatial, temporal and 3DV-VA constraints. Finally, seam choice and carving operation is conducted to generate a retargeted 3D video. Experimental results on 2 types of 3D video sequences shows that the proposed approach produces better seam carving results than the related existing strategies.

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