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Superpixels for image and video processing based on proximity-weighted patch matching

Authors
Lee, Se-HoJang, Won-DongKim, Chang-Su
Issue Date
5월-2020
Publisher
SPRINGER
Keywords
Superpixel; Temporal superpixel; Image segmentation; Saliency detection; Image processing; Video processing
Citation
MULTIMEDIA TOOLS AND APPLICATIONS, v.79, no.19-20, pp.13811 - 13839
Indexed
SCIE
SCOPUS
Journal Title
MULTIMEDIA TOOLS AND APPLICATIONS
Volume
79
Number
19-20
Start Page
13811
End Page
13839
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/56121
DOI
10.1007/s11042-019-08438-8
ISSN
1380-7501
Abstract
In this paper, a temporal superpixel algorithm using proximity-weighted patch matching (PPM) is proposed to yield temporally consistent superpixels for image and video processing. PPM estimates the motion vector of a superpixel robustly, by considering the patch matching distances of neighboring superpixels as well as the superpixel itself. In each frame, we initialize superpixels by transferring the superpixel labels of the previous frame using PPM motion vectors. Then, we update the superpixel labels of boundary pixels by minimizing a cost function, which is composed of feature distance, compactness, contour, and temporal consistency terms. Finally, we carry out superpixel splitting, merging, and relabeling to regularize superpixel sizes and correct inaccurate labels. Extensive experimental results confirm that the proposed algorithm outperforms the state-of-the-art conventional algorithms significantly. Also, it is demonstrated that the proposed algorithm can be applied to video object segmentation and video saliency detection tasks.
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공과대학 (전기전자공학부)
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