Entropy rate superpixel segmentation

We propose a new objective function for superpixel segmentation. This objective function consists of two components: entropy rate of a random walk on a graph and a balancing term. The entropy rate favors formation of compact and homogeneous clusters, while the balancing function encourages clusters with similar sizes. We present a novel graph construction for images and show that this construction induces a matroid - a combinatorial structure that generalizes the concept of linear independence in vector spaces. The segmentation is then given by the graph topology that maximizes the objective function under the matroid constraint. By exploiting submodular and mono-tonic properties of the objective function, we…

• ME
  Mitsubishi Electric Research Laboratories
• NC
  North China University of Technology
• MU
  Multidisciplinary University Research Initiative
• OO
  Office of Naval Research