Depth recovery using an adaptive color-guided auto-regressive model
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Depth enhancement by fusion for passive and active sensing
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Guided depth enhancement via a fast marching method
Image and Vision Computing
Stereo/multiview picture quality: Overview and recent advances
Image Communication
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This paper presents a novel approach for depth video enhancement. Given a high-resolution color video and its corresponding low-quality depth video, we improve the quality of the depth video by increasing its resolution and suppressing noise. For that, a weighted mode filtering method is proposed based on a joint histogram. When the histogram is generated, the weight based on color similarity between reference and neighboring pixels on the color image is computed and then used for counting each bin on the joint histogram of the depth map. A final solution is determined by seeking a global mode on the histogram. We show that the proposed method provides the optimal solution with respect to $L_{1}$ norm minimization. For temporally consistent estimate on depth video, we extend this method into temporally neighboring frames. Simple optical flow estimation and patch similarity measure are used for obtaining the high-quality depth video in an efficient manner. Experimental results show that the proposed method has outstanding performance and is very efficient, compared with existing methods. We also show that the temporally consistent enhancement of depth video addresses a flickering problem and improves the accuracy of depth video.