Fuzzy Knowledge-Based Image Annotation Refinement (CROSBI ID 628402)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Ivašić-Kos, Marina ; Pobar, Miran ; Ribarić, Slobodan
engleski
Fuzzy Knowledge-Based Image Annotation Refinement
Automatic image annotation methods automatically assign labels to images in order to facilitate tasks such as image retrieval. Incorrect labels may negatively influence the search results so image annotation should be as accurate as possible. Labels pertaining to objects or to whole scenes are commonly used for image annotation, and precision is especially important in case when scene labels are inferred from objects, as errors in the object labels may propagate to the scene level. To improve the annotation precision, the idea is to infer which labels are incorrect using the context of other labels and the knowledge about objects and their relations. This procedure is here referred to as annotation refinement. The proposed approach used in this paper includes a fuzzy knowledge base and uses the fuzzy inference algorithms to detect and discard automatically obtained object labels that do not fit the context of other detected objects.
automatic image annotation ; annotation refinement ; fuzzy knowledge representation scheme ; fuzzy inference
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Podaci o prilogu
284-290.
2015.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'15
Arabnia, Hamid R. ; Deligiannidis, Leonidas ; Tinetti, Fernando G.
Las Vegas (NV): The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)
1-60132-404-9
Podaci o skupu
International Conference on Image Processing, Computer Vision, and Pattern Recognition IPCV'15
predavanje
27.07.2015-30.07.2015
Las Vegas (NV), Sjedinjene Američke Države
Povezanost rada
Informacijske i komunikacijske znanosti, Računarstvo