Graph-based Poisson learning for image co-segmentation

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Graph-based Poisson learning for image co-segmentation

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2021

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This paper focuses on applying the state-of-the-art graph-based semi-supervised learning algorithm Poisson Learning to the task of image co-segmentation. The weighted matrix built based on the image texture is used as the feature to do the classification by Poisson learning. The results presented in the paper show that Poisson learning does a good job in segmentation and has high accuracy at very low label rates. Moreover, Poisson learning is tolerant with multi-weight metrics and simple to implement.

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Faculty advisor: Jeff Calder

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This research was supported by the Undergraduate Research Opportunities Program (UROP).

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Ke, Siqi. (2021). Graph-based Poisson learning for image co-segmentation. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/220177.

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