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Superpixel Hierarchy

delete2018-10-01
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OA
AI
X
Xing Wei
Q
Qingxiong Yang
Y
Yihong Gong
N
Narendra Ahuja
M
Ming–Hsuan Yang *
DOI:10.1109/TIP.2018.2836300delete
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Abstract

Abstract

En 中文
Superpixel segmentation has been one of the most important tasks in computer vision. In practice, an object can be represented by a number of segments at finer levels with consistent details or included in a surrounding region at coarser levels. Thus, a superpixel segmentation hierarchy is of great importance for applications that require different levels of image details. However, there is no method that can generate all scales of superpixels accurately in real time. In this paper, we propose the superhierarchy algorithm which is able to generate multiscale superpixels as accurately as the state-of-the-art methods but with one to two orders of magnitude speed-up. The proposed algorithm can be directly integrated with recent efficient edge detectors to significantly outperform the state-of-the-art methods in terms of segmentation accuracy. Quantitative and qualitative evaluations on a number of applications demonstrate that the proposed algorithm is accurate and efficient in generating a hierarchy of superpixels.
Keywords:
Superpixel
segmentation
Boruvka algorithm
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Journal

IEEE Transactions on Image Processing cover
IEEE Transactions on Image Processing
IF:
13.7
Papers:
1.0W
Citations:
8.4W

Organization

X
xi'an jiaotong university
Scholars:
9.2W
Papers: 6.6W
Citations: 75
U
University of Illinois Urbana-Champaign
Scholars:
2.4W
Papers: 2.0W
Citations: 35
University of Illinois System cover
University of Illinois System
Scholars:
6.8W
Papers: 6.2W
Citations: 644
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