Efficient Pose and Cell Segmentation using Column Generation
Computer Vision and Pattern Recognition
2016-12-02 v1
Abstract
We study the problems of multi-person pose segmentation in natural images and instance segmentation in biological images with crowded cells. We formulate these distinct tasks as integer programs where variables correspond to poses/cells. To optimize, we propose a generic relaxation scheme for solving these combinatorial problems using a column generation formulation where the program for generating a column is solved via exact optimization of very small scale integer programs. This results in efficient exploration of the spaces of poses and cells.
Keywords
Cite
@article{arxiv.1612.00437,
title = {Efficient Pose and Cell Segmentation using Column Generation},
author = {Shaofei Wang and Chong Zhang and Miguel A. Gonzalez-Ballester and Julian Yarkony},
journal= {arXiv preprint arXiv:1612.00437},
year = {2016}
}