Computer Science ›› 2015, Vol. 42 ›› Issue (1): 297-302.doi: 10.11896/j.issn.1002-137X.2015.01.066

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Combination of Nearest Neighbor with Semantic Distance for Image Annotation

WU Wei, GAO Guang-lai and NIE Jian-yun   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Most of the nearest neighbor (NN) based image annotation or classification methods do not achieve desired performances.The main reason is that much valuable information is lost when extracting visual features from image.A novel nearest neighbor method was proposed.Firstly,we obtained a new image semantic distance learned by distance metric learning (DML) using image class information,and then multiple clustering centers were formed based on this learned semantic distance.Finally,we constructed our NN model by calculating the distances between the image and these clusters.Our model can minimize the semantic gap for intra-class variations and inter-class similarities.Experimental results on image annotation task of ImageCLEF2012 confirm that our method is efficient and competitive compared with the traditional and state of the art classifiers.

Key words: Image annotation,Feature extraction,Nearest neighbor,Distance metric learning,Semantic distance

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