Journal of Systems Engineering and Electronics ›› 2011, Vol. 22 ›› Issue (1): 150-156.doi: 10.3969/j.issn.1004-4132.2011.01.020
• ELECTRONICS TECHNOLOGY •
Lining Gao1, Fukun Bi2, and Jian Yang1,*
It is of great significance to rapidly detect targets in large-field remote sensing images, with limited computation resources. Employing relative achievements of visual attention in perception psychology, this paper proposes a hierarchical attention based model for target detection. Specifically, at the preattention stage, before getting salient regions, a fast computational approach is applied to build a saliency map. After that, the focus of attention (FOA) can be quickly obtained to indicate the salient objects. Then, at the attention stage, under the FOA guidance, the high-level visual features of the region of interest are extracted in parallel. Finally, at the post-attention stage, by integrating these parallel and independent visual attributes, a decision-template based classifier fusion strategy is proposed to discriminate the task-related targets from the other extracted salient objects. For comparison, experiments on ship detection are done for validating the effectiveness and feasibility of the proposed model.
Lining Gao, Fukun Bi, and Jian Yang. Visual attention based model for target detection in large-field images[J]. Journal of Systems Engineering and Electronics, 2011, 22(1): 150-156.
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