Volume 8, Issue 3, June 2015, Pages 530 - 538
Chemical Reaction Optimization for Feature Combination in Bio-inspired Visual Attention
- Lu Gan, Haibin Duan
- Corresponding Author
- Lu Gan
Available Online 1 June 2015.
- https://doi.org/10.1080/18756891.2015.1036220How to use a DOI?
- bio-inspired visual attention, Chemical Reaction Optimization (CRO), feature combination, saliency
- Bio-inspired visual attention models human visual system to detect the most salient part of a visual field. In the existing diversified computational models, bottom-up visual attention that works out a saliency map to indicate the conspicuity of visual stimuli in an image has gained much popularity. This paper introduces a task-driven training procedure into the basic bottom-up computational model to make bio-inspired visual attention more intelligent and appropriate for a particular visual task. Chemical Reaction Optimization (CRO) is a recently proposed evolutionary metaheuristic, simulating the dynamic interaction of molecules in a chemical reaction. In this paper, CRO algorithm is used to optimize the weight coefficients for feature combination through the training procedure. Experimental results show that CRO algorithm outperforms other evolution algorithms in bio-inspired visual attention.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Lu Gan AU - Haibin Duan PY - 2015 DA - 2015/06 TI - Chemical Reaction Optimization for Feature Combination in Bio-inspired Visual Attention JO - International Journal of Computational Intelligence Systems SP - 530 EP - 538 VL - 8 IS - 3 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2015.1036220 DO - https://doi.org/10.1080/18756891.2015.1036220 ID - Gan2015 ER -