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Parameter-free image segmentation with SLIC
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DOI：10.1016/j.neucom.2017.05.096.png)
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Abstract
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In this paper, we develop a parameter-free image segmentation framework using Simple Linear Iterative Clustering (SLIC) and Extreme Learning Machines (ELM). SLIC requires a single parameter, the number of centroids k. Our framework, called PF-SLIC (Parameter-Free SLIC) uses an ELM to predict the optimal k, generating a parameter-free framework. PF-SLIC and its streaming variant SPF-SLIC (Streaming PF-SLIC) achieve performance comparable to other models on ultra-high-definition (4K) images and streams, with runtimes orders of magnitude lower. (c) 2017 Elsevier B.V. All rights reserved.
Keywords:
SLIC
ELM
Image segmentation
Superpixel
Streaming
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