Paper Info
Title
Fuzzy based contextual cueing for region level annotation.
Abstract
This paper investigates the challenging issue of assigning given image-level annotations to precise regions on natural images. We propose a novel label to region assignment (LRA) technique called Fuzzy-based Contextual-cueing Label Propagation (FCLP) with four parts: First, an image is over-segmented into a set of atomic patches and the local visual information of color features and texture features are extracted. Second, fuzzy representation and fuzzy reasoning are used to model contextual cueing information, especially for the imprecise position information and ambiguous spatial topological relationships. Third, labels are propagated inter images in visual space and intra images in contextual cueing space. Finally, the fuzzy C-means clustering based on K-nearest neighbor (KNN-FCM) is utilized to segment the images into semantic regions and associate with corresponding annotations. Experiments on the public datasets demonstrate the effectiveness of the proposed technique.
Year
DOI
Venue
2010
10.1145/1937728.1937729
ICIMCS
Keywords
Field
DocType
region level annotation,contextual cueing,fuzzy reasoning,visual space,label to region assignment,proposed technique,contextual cueing information,fuzzy theory,fuzzy c-means,imprecise position information,k-nearest neighbor,fuzzy representation,contextual cueing space,local visual information,k nearest neighbor
Computer vision,Visual space,Annotation,Fuzzy reasoning,Fuzzy classification,Pattern recognition,Label propagation,Computer science,Contextual cueing,Fuzzy logic,Artificial intelligence,Cluster analysis
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
4
Name
Order
Citations
PageRank
Sheng-hua Zhong122018.58
Liu Yan282841.20
Yang Liu3936.81
Fu-lai Chung424434.50