基于原型对象和主题模型的显著性检测

Zhidong Li, Jie Xu, Yang Wang, G. Geers, Jun Yang
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引用次数: 4

摘要

本文提出了一种新的显著性检测计算框架,将显著性图计算与原目标检测相结合。基于显著性图,利用潜在主题模型对原型对象进行检测。然后利用检测到的原始目标来改进显著性图的计算。在两个公开可用的数据集上进行了广泛的实验。实验结果表明,所提出的框架优于现有的方法。
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Saliency detection based on proto-objects and topic model
This paper proposes a novel computational framework for saliency detection, which integrates the saliency map computation and proto-objects detection. The proto-objects are detected based on the saliency map using latent topic model. The detected proto-objects are then utilized to improve the saliency map computation. Extensive experiments are performed on two publicly available datasets. The experimental results show that the proposed framework outperforms the state-of-art methods.
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