Temporal and Spatial Denoising of Depth Maps
Date Issued
2014
Date
2014
Author(s)
Tseng, Po-Jui
Abstract
This work presents a refinement procedure of depth map acquired by RGB-D(Depth) cameras. With the release of many new structured-light RGB-D cameras,such as Microsoft Kincet or Asus Xtion PRO LIVE, it is very conventional and consumer-accessible to acquire high-resolution depth maps. This 3D depth information can be applied to many fields, like augmented reality, image processing,and 3D printer. However, RGB-D cameras suffered from problems such as undesired occlusion, inaccuracy of depth value, and temporal variation. To broaden its application, it is crucial to solve the above-mentioned problems. Thus, The proposed
novel algorithm based on the exemplar-based inpainting method to cope with the artifact in RGB-D cameras’ depth maps. This exemplar-based inpainting has been used to repair an object-removed image with missing information. The idea of this inpainting method is similar to the procedure of padding the occlusions of RGB-D cameras’ depth data. Therefore, the proposed method enhances and adjusts the
inpainting method to fit and refine the image quality of RGB-D cameras’ depth data. For evaluating the experiment results, our proposed method will be tested on Tsukuba
Stereo Dataset, which provides a 3D video with ground truth of depth maps, occlusion maps, and RGB images, PSNR, and computational time as evaluation metrics. Moreover, a set of self-shooting RGB-D depth maps and their refinement results will also be shown to prove the improvement of our performance compared with the original occluded depth maps.
Subjects
深度影像
Asus Xtion PRO LIVE
Kinect
RGB-D 攝影機
影像修補
Type
thesis
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