视觉显著性凸显目标的评价

为了全面评价显著图'凸显'目标的程度, 本文建立了一系列定量指标来评价目前备受关注的五种显著图模型在目标分割中的作用. 首先,简要回顾了五种显著图模型;其次,以人工分割作为显示图像中感兴趣目标的标准,建立了三组评价指标 (分别对应原始显著图、固定阈值以及自适应阈值的分割图);最后,在Corel、MSRA、Weizmann等图像数据库上进行了评价实验,结果显示了五种显著图模型在目标分割中的不同性能.本文的研究对基于显著性目标分割方法的进一步发展和应用具有一定的意义和参考价值.

To Evaluate Salience Map towards Popping out Visual Objects

The aim of this paper is to present a quantitative evaluation of five popular salience maps for object segmentation. First, five salience maps are revisited in terms of theory foundation. Second, human segmentation is taken as the ground truth of interesting objects 'pop-out' to build three quantitative evaluation ratios of salience map to human segmentation. Finally, evaluation experiments are conducted on three image databases of Corel, MSRA and Weizmann. Results show some insights into the performances of these different salience maps in object segmentation. This research is believed meaningful and useful for the further development of salience-driven methods for object segmentation.