Parameter-free image segmentation with SLIC

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.