depth estimation is a crucial step for 2d/3dconversion from monoscopic video. In this paper, a novel method for depth estimation from motion with camera motion is proposed. In the proposed method, image matching usin...
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ISBN:
(纸本)9781479923410
depth estimation is a crucial step for 2d/3dconversion from monoscopic video. In this paper, a novel method for depth estimation from motion with camera motion is proposed. In the proposed method, image matching using critical point filters is applied to extract the pixel-level motion field for each frame. As camera motion can bring pseudo motion vectors by image matching, and thus leading to depth ambiguity. To solve this problem, we propose to estimate the camera moving model using robust RANSAC algorithm. Then, the initial depth map is estimated by using the motion vectors without camera motion. Finally, the depth values of the pixels at the edges of moving objects are refined using a post filter based on homogeneous points. Experimental results show that the proposed method achieves considerable performances on depth map in presence of camera motion.
depth propagation is an effective and efficient way to produce depth maps for a video sequence. Motion estimation in most existing depth propagation schemes is performed only based on the estimateddepth maps without ...
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ISBN:
(纸本)9781479902880
depth propagation is an effective and efficient way to produce depth maps for a video sequence. Motion estimation in most existing depth propagation schemes is performed only based on the estimateddepth maps without consideration for color information. This paper presents a novel key frame depth propagation algorithm combining bilateral filtering and motion estimation. A color guided motion estimation process is proposed by taking both color anddepth information into account when estimating the motion vectors. In addition, a bidirectional propagation strategy is adopted to reduce the accumulation of depth errors. Experimental results show that the proposed algorithm outperforms most of the existing techniques in obtaining high quality depth maps indicating a better effect of the synthesized stereoscopic video.
depth estimation is a crucial step for 2d/3dconversion from monoscopic video. In this paper, a novel method for depth estimation from motion with camera motion is proposed. In the proposed method, image matching usin...
详细信息
ISBN:
(纸本)9781479923427
depth estimation is a crucial step for 2d/3dconversion from monoscopic video. In this paper, a novel method for depth estimation from motion with camera motion is proposed. In the proposed method, image matching using critical point filters is applied to extract the pixel-level motion field for each frame. As camera motion can bring pseudo motion vectors by image matching, and thus leading to depth ambiguity. To solve this problem, we propose to estimate the camera moving model using robust RANSAC algorithm. Then, the initial depth map is estimated by using the motion vectors without camera motion. Finally, the depth values of the pixels at the edges of moving objects are refined using a post filter based on homogeneous points. Experimental results show that the proposed method achieves considerable performances on depth map in presence of camera motion.
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