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Edge-aware depth image filtering using color segmentation
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AI
DOI：10.1016/j.patrec.2014.03.026.png)
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摘要
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High-quality depth maps are essential to many tasks in 3D vision. Especially depth maps generated with one of the recently upcoming low-cost 3D scanners need postprocessing to enhance depth quality. In this paper, we focus on one special aspect of depth quality: The alignment of color and depth edges in video-plus-depth sequences. Even with calibrated depth sensors, depth edges usually do not fully align with the edges of the color stream. We present a new depth enhancement method based on color segmentation that aligns depth edges with color edges. We also introduce a new assessment method called Edge Accuracy Test (EAT) to quantify the ability of a depth enhancement algorithm to care for aligned edges. We publish the video-plus-depth sequences of EAT so that other researchers can perform EAT on their algorithms. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Depth
Depth filtering
Depth processing
Depth quality
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3.3
论文数:
7.9K
被引数:
1.6W
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