A swarm optimization model for energy minimization problem of early vision

Authors:
Wenhui Zhou;Lili Lin;Weikang Gu
Affiliations:
Department of Information Science and Electronic Engineering, ZheJiang University, HangZhou, China;College of Information and Electronic Engineering, ZheJiang Gongshang University, Hangzhou, China;Department of Information Science and Electronic Engineering, ZheJiang University, HangZhou, China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Year:
2006

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Abstract

This paper proposes a swarm optimization model for energy minimization problem of early vision, which is based on a multi-colony ant scheme. Swarm optimization is a new artificial intelligence field, which has been proved suitable to solve various combinatorial optimization problems. Compared with general optimization problems, energy minimization of early vision has its unique characteristics, such as higher dimensions, more complicate structure of solution space, and dynamic constrain conditions. In this paper, the vision energy functions are optimized by repeatedly minimizing a certain number of sub-problems according to divide-and-conquer principle, and each colony is allocated to optimize one sub-problem independently. Then an appropriate information exchange strategy between neighboring colonies, and an adaptive method for dynamic problem are applied to implement global optimization. As a typical example, stereo correspondence will be solved using the proposed swarm optimization model. Experiments show this method can achieve good results.