Interactive cosegmentation using global and local energy optimization

Dong, Xingping, Shen, Jianbing, Shao, Ling and Yang, Ming-Hsuan (2015) Interactive cosegmentation using global and local energy optimization. IEEE Transactions on Image Processing, 24 (11). pp. 3966-3977. ISSN 1057-7149

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We propose a novel interactive cosegmentation method using global and local energy optimization. The global energy includes two terms: 1) the global scribbled energy and 2) the interimage energy. The first one utilizes the user scribbles to build the Gaussian mixture model and improve the cosegmentation performance. The second one is a global constraint, which attempts to match the histograms of common objects. To minimize the local energy, we apply the spline regression to learn the smoothness in a local neighborhood. This energy optimization can be converted into a constrained quadratic programming problem. To reduce the computational complexity, we propose an iterative optimization algorithm to decompose this optimization problem into several subproblems. The experimental results show that our method outperforms the state-of-the-art unsupervised cosegmentation and interactive cosegmentation methods on the iCoseg and MSRC benchmark data sets.

Item Type: Article
Uncontrolled Keywords: co-segmentation, Gaussian mixture model, histogram matching, local spline regression, optimization
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Ay Okpokam
Date Deposited: 25 Aug 2015 08:39
Last Modified: 13 Oct 2019 00:21

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