Region-based semi-automatic annotation using the Bag of Words representation of the keywords
Automatic Image Annotation (AIA) tries to minimize the manual effort for image annotation. However, the performance of the AIA approaches is not satisfactory. The interaction of user is needed to solve this problem. The annotation is refined during the interaction by using semantic-based relevance feedback. This approach has a limit as only the annotations of found images during the interaction are updated. In this paper we introduce a novel method of semi-automatic annotation. The method is using visual feature representations of keywords which are improved during the region-based relevance feedback. The experiments show that this method gives good results and can be used to update the annotations for all images.
Nhu Van NGUYEN Alain BOUCHER Jean-Marc OGIER Salvatore TABBONE
L3i - University of La Rochelle, 17042 La Rochelle cedex 1, France Institut de la Francophonie pour Institut de la Francophonie pour lInformatique, MSI, UMI 209, Hanoi, Vietnam IRD, UMI 209, UMMISCO, L3i - University of La Rochelle, 17042 La Rochelle cedex 1, France QGAR - LORIA - University of Nancy 2, BP 239 - 54506 Vandoeuvre-les-Nancy, France
国际会议
The Fifth International Conference on Image and Graphics(第五届国际图像图形学学术会议 ICIG 2009)
西安
英文
422-427
2009-09-20（万方平台首次上网日期，不代表论文的发表时间）