WISA: a novel web image semantic analysis system

Authors:
Hongtao Xu;Xiangdong Zhou;Lan Lin
Affiliations:
Fudan University, Shanghai, China;Fudan University, Shanghai, China;Tongji University, Shanghai, China
Venue:
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2008

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Abstract

We present a novel Web Image Semantic Analysis (WISA) system, which explores the problem of adaptively modeling the distributions of the semantic labels of the web image on its surrounding text. To deal with this problem, we employ a new piecewise penalty weighted regression model to learn the weights of the contributions of the different parts of the surrounding text to the semantic labels of images. Experimental results on a real web image data set show that it can improve the performance of web image semantic annotation significantly.