What Do Datasets Say About Saliency Models?

被引:0
|
作者
Pardo, Xose M. [1 ]
Fdez-Vidal, Xose R. [1 ]
机构
[1] Univ Santiago de Compostela, Ctr Singular Invest Tecnol Informac CiTIUS, Santiago De Compostela 15782, Spain
关键词
Visual attention; Video saliency; Feature selection; VISUAL-ATTENTION;
D O I
10.1007/978-3-319-58838-4_12
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Given the amount and variety of saliency models, the knowledge of their pros and cons, the applications they are more suitable for, or which are the more challenging scenes for each of them, would be very useful for the progress in the field. This assessment can be done based on the link between algorithms and public datasets. In one hand, performance scores of algorithms can be used to cluster video samples according to the pattern of difficulties they pose to models. In the other hand, cluster labels can be combined with video annotations to select discriminant attributes for each cluster. In this work we seek this link and try to describe each cluster of videos in a few words.
引用
收藏
页码:104 / 113
页数:10
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