Cooperative Optimization for Energy Minimization: A Case Study of Stereo Matching
Abstract
Often times, individuals working together as a team can solve hard problems beyond the capability of any individual in the team. Cooperative optimization is a newly proposed general method for attacking hard optimization problems inspired by cooperation principles in team playing. It has an established theoretical foundation and has demonstrated outstanding performances in solving real-world optimization problems. With some general settings, a cooperative optimization algorithm has a unique equilibrium and converges to it with an exponential rate regardless initial conditions and insensitive to perturbations. It also possesses a number of global optimality conditions for identifying global optima so that it can terminate its search process efficiently. This paper offers a general description of cooperative optimization, addresses a number of design issues, and presents a case study to demonstrate its power.
Cite
@article{arxiv.cs/0701057,
title = {Cooperative Optimization for Energy Minimization: A Case Study of Stereo Matching},
author = {Xiaofei Huang},
journal= {arXiv preprint arXiv:cs/0701057},
year = {2007}
}