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Fast Minimax Path-Based Joint Depth Interpolation

delete2015-05-01
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PRE
AI
L
Longquan Dai *
F
Feihu Zhang
X
Xing Mei
X
Xiaopeng Zhang
DOI:10.1109/LSP.2014.2365527delete
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Abstract

Abstract

En 中文
We propose a fast minimax path-based depth interpolation method. The algorithm computes for each target pixel varying contributions from reliable depth seeds, and weighted averaging is used to interpolate missing depths. Compared with state-of-the-art joint geodesic upsampling method which selects the K nearest seeds to interpolate missing depths with O(Kn) complexity, our method does not need to limit the number of seeds to K and reduces the computational complexity to O(n). In addition, the minimax path chooses a path with the smallest maximum immediate pairwise pixel difference on it, so it tends to preserve sharp depth discontinuities better. In contrast to the results of previous depth upsampling algorithms, our approach can provide accurate depths with fewer artifacts.
Keywords:
Depth map
minimax path
upsampling
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Signal Processing Magazine cover
IEEE Signal Processing Magazine
IF:
9.6
Papers:
1.1W
Citations:
1.7W

Organization

C
chinese academy of sciences
Scholars:
56.3W
Papers: 44.8W
Citations: 704