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In the past decades, hundreds of saliency models have been proposed for fixation prediction, along with dozens of evaluation metrics. However, existing metrics, which are often heuristically designed, may draw conflict conclusions in comparing saliency models. As a consequence, it becomes somehow confusing on the selection of metrics in comparing new models(More)
In this paper we propose a novel semantic label transfer method using supervised geodesic propagation (SGP). We use supervised learning to guide the seed selection and the label propagation. Given an input image, we first retrieve its similar image set from annotated databases. A Joint Boost model is learned on the similar image set of the input image. Then(More)
This paper presents a semantic labeling framework with geodesic propagation (GP). Under the same framework, three algorithms are proposed, including GP, supervised GP (SGP) for image, and hybrid GP (HGP) for video. In these algorithms, we resort to the recognition proposal map and select confident pixels with maximum probability as the initial propagation(More)
D-S evidence theory has been widely used in various fields of information fusion due to its efficiency in dealing with uncertain information. Unfortunately, combination of conflicting evidences with the classical Dempster's rule may produce the counter-intuitive results. In this paper, Definitions of correlation coefficient and credibility are first(More)
The intuitionistic fuzzy set, as a generation of Zadeh’ fuzzy set, can express and process uncertainty much better, by introducing hesitation degree. Similarity measures between intuitionistic fuzzy sets (IFSs) are used to indicate the similarity degree between the information carried by IFSs. Although several similarity measures for intuitionistic fuzzy(More)
As a generation of fuzzy set theory, intuitionistic fuzzy (IF) set theory has received considerable attention for its capability on dealing with uncertainty. Similarity measures of IF sets are used to indicate the degree of commonality between IF sets. Although several similarity measures for IF sets have been proposed in previous studies, some of those(More)
Error correcting output codes (ECOCs) is a powerful framework to solve the multi-class problems. Finding the optimal partitions with maximum class discrimination efficiently is a key point to improve its performance. In this paper, we propose an alternative and efficient approach to obtain the partitions which are discriminative in the class space. The main(More)