Superdifferential Cuts for Binary Energies

Tatsunori Taniai, Yasuyuki Matsushita, Takeshi Naemura; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 2030-2038

Abstract


We propose an efficient and general purpose energy optimization method for binary variable energies used in various low-level vision tasks. The proposed method can be used for broad classes of higher-order and pairwise non-submodular functions. We first revisit a submodular-supermodular procedure (SSP) [Narasimhan05], which is previously studied for higher-order energy optimization. We then present our method as generalization of SSP, which is further shown to generalize several state-of-the-art techniques for higher-order and pairwise non-submodular functions [Ayed13, Gorelick14, Tang14]. In the experiments, we apply our method to image segmentation, deconvolution, and binarization, and show improvements over state-of-the-art methods.

Related Material


[pdf]
[bibtex]
@InProceedings{Taniai_2015_CVPR,
author = {Taniai, Tatsunori and Matsushita, Yasuyuki and Naemura, Takeshi},
title = {Superdifferential Cuts for Binary Energies},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}