Automatic 2D-to-3D video conversion technique based on depth-from-motion and color segmentation

Abstract

Abstract-Most of the TV manufacturers have released 3DTVs in the summer of 2010 using shutter-glasses technology. 3D video applications are becoming popular in our daily life, especially at home entertainment. Although more and more 3D movies are being made, 3D video contents are still not rich enough to satisfy the future 3D video market. There is a rising demand on new techniques for automatically converting 2D video content to stereoscopic 3D video displays. In this paper, an automatic monoscopic video to stereoscopic 3D video conversion scheme is presented using block-based depth from motion estimation and color segmentation for depth map enhancement. The color based region segmentation provides good region boundary information, which is used to fuse with block-based depth map for eliminating the staircase effect and assigning good depth value in each segmented region. The experimental results show that this scheme can achieve relatively high quality 3D stereoscopic video output.

A Fast Depth-Map Generation Algorithm based on Motion Search from 2D Video Contents

“…The test results are shown in Table 1. According to Table 1,we can easily find that the efficiency of our method is better than the algorithms in [12] and [13], about 31% of time saving than [12] and 65% to [13]. The promotion is especially remarkably in CAR PHONE and COASTGUARD for the large scale of smooth area in these two sequences.…”

“…To evaluate our proposed algorithm, several test sequences are used to perform the [12] ， [13] and our method to make some comparisons on the efficiency. We set the threshold of Sobel to 5000 while the thresholds of motion search modules are 0.15 and 0.3.…”

“…Finally the bilateral filter is adopted to eliminate the block effect and the staircase edges that remained in the fused depth-maps. The results show that with the proposed algorithm a smooth and reliable depth-map and a better visual 3D video can be obtained with low computational complexity compared to the methods in [12] and [13].…”

“…But the DFM requires that moving objects must exist in successive frames. Fusion with color information can improve the depth-map quality [12] [13]. In the literature [12], the depth-map generated from motion-parallax is fused with color segmentation to obtain a clear and reliable depth-map, but its color segmentation algorithm introduces high computational complexity.…”

“…Fusion with color information can improve the depth-map quality [12] [13]. In the literature [12], the depth-map generated from motion-parallax is fused with color segmentation to obtain a clear and reliable depth-map, but its color segmentation algorithm introduces high computational complexity. In the literature [13] motion estimation is performed by using luminance and chrominance information in motion search module to yield a reliable depth-map and reduce the computation complexity.…”