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Visual attention model for target search in cluttered scene

机译:杂乱场景中目标搜索的视觉注意模型

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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.
机译:视觉注意力模型产生显着图,其中细心区域对于场景的剩余部分更为独特。 在这项工作中,提出了一种新的定向映射图(OCM)以计算显着性。 所提出的方法基于具有正交取向的Gabor滤波器输出的差异,因为车辆是该研究中搜索任务的目标。 此外,作为另一个贡献,根据场景中的目标距离的输入图像的选择性分辨率,也用于所提出的方案,以便目标搜索的益处。 实验结果表明,OCM模型和输入图像的选择性分辨率都产生了对杂乱场景中目标搜索的有希望的结果。

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