Predator-Prey Biogeography-Based Optimization for Bio-inspired Visual Attention

DOI

10.1080/18756891.2013.820957How to use a DOI?

Keywords

Biogeography-Based Optimization (BBO), visual attention, saliency, feature combination, predator-prey

Abstract

Visual attention mechanism is one of the important techniques in computer vision field, and it can increase the effectiveness of computer image information processing. Biogeography-Based Optimization (BBO) is a bioinspired algorithm for global optimization, searching for the global optimum mainly through two steps: migration and mutation. In this paper, a novel Predator-Prey Biogeography-Based Optimization (PPBBO) is utilized to solve the bio-inspired visual attention problem. In PPBBO method, BBO is combined with the mechanism of predatorprey, which can enhance the global convergence of the algorithm. The convergence property of the PPBBO is analyzed theoretically, and the detailed process is also given. Comparative experimental results with basic BBO, CBBO, CPPBBO, and Particle Swarm Optimization (PSO) demonstrate the feasibility and effectiveness of our presented PPBBO for adjusting combination of feature maps in visual attention.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Xiaohua Wang
AU  - Haibin Duan
PY  - 2013
DA  - 2013/11/01
TI  - Predator-Prey Biogeography-Based Optimization for Bio-inspired Visual Attention
JO  - International Journal of Computational Intelligence Systems
SP  - 1151
EP  - 1162
VL  - 6
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2013.820957
DO  - 10.1080/18756891.2013.820957
ID  - Wang2013
ER  -