Visual attention model for target search in cluttered scene

Nevrez Imamoglu, Weisi Lin
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引用次数: 1

Abstract

Visual attention models generate saliency maps in which attentive regions are more distinctive with respect to remaining parts of the scene. In this work, a new model of orientation conspicuity map (OCM) is presented for the computation of saliency. The proposed method is based on the difference of the Gabor filter outputs with orthogonal orientations because vehicles are the targets for the search tasks in this study. Moreover, as another contribution, selective resolution for the input image, according to the distance of the target in the scene, is also utilized with the proposed scheme for the benefit to target search. Experimental results demonstrate that both the OCM model and selective resolution for input images yield promising results for the target search in cluttered scenes.
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杂乱场景下目标搜索的视觉注意模型
视觉注意模型生成显著性地图,其中注意区域相对于场景的其余部分更具独特性。本文提出了一种新的方向显著性图(OCM)模型,用于显著性的计算。由于车辆是本研究中搜索任务的目标,因此提出的方法是基于正交方向的Gabor滤波器输出的差异。此外,该方案还根据目标在场景中的距离对输入图像进行了选择性分辨率,有利于目标搜索。实验结果表明,OCM模型和输入图像的选择性分辨率对混乱场景下的目标搜索都有很好的效果。
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