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 information embedded in the depth and color video should be taken into consideration simultaneously. In this paper, we propose an energy-constrained video retargeting approach for color-plus-depth 3D video. We first build a 3D video visual attention (3DV-VA) computation model by combining gradient, saliency, motion and depth information. Then, an energy function is generated using spatial, temporal and 3DV-VA constraints. Finally, seam selection and carving operation is conducted to generate a retargeted 3D video. Experimental results on two types of 3D video sequences shows that the proposed approach produces better seam carving results than the related existing methods.